680 Data Scientist jobs in Washington

Overview

Job Title: Data scientist

Location: Long Beach, WA (Onsite)

Duration: Fulltime

• Experience in executing projects in Agile Framework
• Understanding of machine learning and deep learning frameworks
• Understanding of generative models (e.g., GANs, VAEs, Transformers) and natural language processing
• Understanding of natural language processing (NLP)
• Understanding of data preprocessing and model fine-tuning
• Awareness of ethical considerations and bias mitigation strategies
• Proficiency in Python / C#
• Strong analytical and problem-solving skills

Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.

Overview

Evans & Chambers Technology is seeking a highly motivated Data Scientist to join our team. Evans & Chambers partners with the US national defense community to create fully integrated, resilient, and innovative digital solutions that enable them to make smart decisions in real-time. We work with our customers on everything from conquering their data to improving and safeguarding IT infrastructure. Our ultimate goal? To enhance our nation's ability to identify, address, and act – no matter what challenges arise.

Clearance: TS/SCI with CI Poly

Location: Washington, DC and Arlington, VA

• 4-10 plus years’ experience in Data Science or Data Engineering
• Provides comprehensive support for intelligence processing by offering expert guidance on developing solutions for errors detected in collected intelligence data.
• Analyzes inconsistencies, anomalies, and data gaps using advanced analytical tools and machine learning techniques to enhance the accuracy and reliability of intelligence reporting.
• Develops data-driven methodologies to refine data validation processes and optimize error detection within intelligence workflows.
• Assists in researching, understanding, and integrating emerging technologies to improve intelligence processing capabilities and enhance data quality across multiple intelligence disciplines.
• Offers expert guidance on implementing corrective solutions by designing algorithms and automated processes that mitigate systemic errors in intelligence collection.
• Applies statistical modeling, data visualization, and predictive analytics to refine intelligence processing techniques and enhance operational decision-making.
• Works with intelligence teams to develop tailored solutions that address data inconsistencies, improve collection methodologies, and streamline analytical processes.
• Provides structured recommendations to strengthen intelligence processing frameworks, optimize resource utilization, and improve overall intelligence data integrity.
• Actively supports Amentum’s implementation of the B2C2WG (Boards, Bureau, Centers, Cells, and Working Groups) model.

• Bachelor of Science in related field
• ICAgile Certified Professional
• IBM Professional Data Scientist

All employment opportunities are made without regard to age, race, creed, color, religion, sex national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status or any other basis protected by law.

Overview

Immigration / Work Authorization Notice: At this time, iSpot does not provide visa sponsorship or immigration support for this role. Applicants must already be authorized to work in the United States on a full-time, permanent basis without the need for current or future sponsorship.

iSpot competes for the best talent. Our compensation packages consist of salary and equity in one of Seattle's hottest start-ups, as well as other standard benefits. Most importantly, we provide a really interesting working experience, and the chance to contribute to the success of something great.

About iSpot : At iSpot, we empower advertisers to measure the true impact of their TV and streaming campaigns—from concept through airing to conversion. Our fast, accurate, and actionable measurement and attribution solutions enable advertisers to evaluate creative effectiveness, optimize media plans, and attribute results across platforms, all while benchmarking against competitors and historical data. With real-time performance insights seamlessly integrated across linear and streaming TV, iSpot equips advertisers to make swift, confident decisions that drive impactful business results.

About the Team : Our Client Data Science team is dedicated to delivering invaluable insights and reports to our clients. We thrive on innovation, employing cutting-edge techniques that empower our clients to advance their businesses. Comprising Analysts, Data Scientists, and Engineers, our team brings a deep understanding of the media landscape, advanced data science techniques, and strong coding skills, all fueled by a passion for growth.

We are seeking a passionate Data Scientist to join our dynamic Client Data Science team. In this role, you will design and develop custom reports tailored to our iSpot clients, providing them with the insights they need to succeed. We are looking for someone who shares our obsession with data accuracy and possesses an insatiable curiosity for learning and tackling challenging goals in a fast-paced environment.

Join us in this collaborative environment, where your contributions will help drive innovation and push the boundaries of the media industry. We cant wait to see how you'll make an impact!

As a key member of the Client Data Science team, you will be responsible for a variety of critical tasks, including :

• Collaborating on complex problems, both independently and as part of a team, while writing and optimizing R, Python, or SQL scripts for effective data processing.
• Adapting existing tools and methods to meet evolving needs, balancing workloads across various projects, and leveraging solid machine learning and statistical skills to inform data-driven decisions.
• Collecting, aggregating, and manipulating data from multiple sources, applying analytical techniques to derive insights, and creating clear visualizations or reports.
• Engaging with internal and external teams to clarify requirements, address challenges, and develop tailored solutions, while documenting project status and updates in tools like JIRA.
• Communicating effectively with diverse audiences, translating complex findings into accessible formats through written reports and presentations, and actively participating in team discussions to support collaboration and problem-solving.

• 5% People Mentorship
• 25% Project Leadership
• 5% Strategy, Planning and Prioritization
• 5% Internal or Client Collaboration
• 60% Hands on : Reporting, Coding, Debugging, Developing, Methods, etc.

• Experience: 3+ years of experience in Data Science, or comparable field
• Education: Bachelor's degree in a quantitative or social science field, Master's preferred
• Coding Experience: 3+ years coding experience and 1+ years coding specifically in R or Python
• Coding Skill: Intermediate coding skill in Python or R
• Leadership Experience: 1+ year of project leadership
• Technical Knowledge: Intermediate knowledge of Data Science, Modeling, Machine Learning, and Statistics
• Communication: Exceptional written and verbal communication with internal and external stakeholders at all levels

iSpot's Client Data Science team expects all candidates to have a range of soft skills, including but not limited to: critical thinking, attention to detail, and effective communication. Additionally, the following soft skills are required for success in this role: Prioritization of accuracy; Flexibility and adaptability; Resourcefulness; Logic.

Target cash compensation range: $95,000 - 118,000 USD Annually

We are committed to providing competitive, market-informed compensation. The cash compensation above includes base salary, variable commission for employees in eligible roles, and annual bonus targets for eligible roles. In addition to cash compensation, all full-time iSpotters are eligible to participate in iSpot's equity plan to receive stock options. Non-exempt roles will also be eligible for (pre-approved) overtime pay. Individual compensation packages are influenced by different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.

For more information on total rewards package, go HERE

iSpot supports a hybrid and flexible workplace. Depending on location and work responsibilities, employees may be designated as full-time or part-time office-based or a fully remote employee. A hybrid work schedule indicates that you work in the office some days and work from home other days. The best hybrid workplaces allow for flexibility while also encouraging consistency.

Those local or living in surrounding areas to one of our offices (Bellevue, WA; El Segundo, CA; New York, NY) will work a hybrid schedule, coming into their local office 1-3 days a week. While those in a role, not office-based and located further away from our offices, will work a fully remote schedule. If you have questions regarding exact details of our hybrid & flexible workplace policy, please let your recruiter know and they will discuss with you further.

LI-Remote

If you don't feel you met every single requirement for the role, don't rule yourself out. Please apply anyway!

iSpot is an equal opportunity employer. All applicants will receive consideration for employment without regard to race, ethnicity, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. If you need assistance and / or a reasonable accommodation due to a disability during the application or the recruiting process, please contact our HR team.

California Residents applying for positions at iSpot can access our California Consumer Privacy Act here.

Meta is seeking a highly skilled and motivated Data Scientist to join our Infrastructure Data Centers team. As a lead data scientist, you will partner with stakeholders, program managers, and other data science functions to translate Meta’s Infrastructure Data Centers’ data into value. You will have the opportunity to work on a wide range of data science projects, such as developing an analytics program to drive operational efficiency, conducting strategic analysis to facilitate decision making, measuring Machine Learning models and automation to increase predictive accuracy and reduce manual effort, and working with software developers to build analytical solutions.The ideal candidate will have a passion for working in ambiguous environment and creating impact from the ground up in a fast-paced environment. Additionally, you will have a proven track record of thought leadership and impact in developing similar analytics programs and machine learning solutions. This position is part of the Infrastructure Data Centers organization.

Data Scientist Responsibilities:

• Collaborate with cross-functional data and business teams to define problems, analyze impacts, identify opportunities, and develop solutions that improve decision-making and efficiency.
• Translate business challenges into data-driven problems and design appropriate data science solutions, including metrics and analytics, business intelligence, experimentation
• Identify operational gaps, build analytical models to derive insights, and support decision-making across organizational leadership.
• Design and implement statistical models such as hypothesis testing, forecasting, statistical process control, and simulation to influence critical business decisions and Data Center operations.
• Utilize expertise in statistics, machine learning, optimization, and automation to develop analytics solutions.
• Work closely with stakeholders, data engineers, and program/product managers to ensure seamless progress.
• Educate and influence stakeholders to enhance operational efficiency with empathy.
• Recommend process improvements based on operational data and user behavior to boost business performance.
• Mentor team members on data science best practices.
  
  

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 6+ years of experience (2 years+ of experience post Ph.D.) with advanced SQL in big data environments (e.g., Hive, Presto, Spark) and data modeling.
• 6+ years of experience (2 years+ of experience post Ph.D.) managing and analyzing large-scale data using Python, R, or similar languages.
• 6+ years of experience (2 years+ of experience post Ph.D.) of working with visualization tools such as Tableau, PowerBI, or similar.
• 6+ years experience (2 years+ of experience post Ph.D.) analyzing and interpreting data, developing metrics, drawing conclusions, recommending actions, and reporting results across stakeholders.
• Experience in enhancing data collection procedures, data processing, cleansing, and verifying the integrity of data used for analysis
• Proven track record of managing and leading cross-functional projects and teams.
• Solid understanding of machine learning techniques and algorithms.
• Hands-on programming experience in one or more of: AI/ML, LLM, NLP, Statistical modeling.
• Proficient in statistical analysis and experimental design.
  
  

• Technical knowledge of data center operations
• Masters degree in Computer Science, Engineering, Mathematics, Statistics, Operations Research, or a related analytical field.
• Knowledge of simulation and optimization techniques
• Great communication and storytelling skills to influence all organizational levels (engineers, executives and cross functional teams) to drive business decisions
  
  

A(n) Data Scientist job in Falls Church, Pentagon, Alexandria, or Arlington Area is currently available through Belcan at one of our key Defense clients. To be considered for this role, you will have a Bachelor's degree in a computer or data science field and minimum 6 years experience of relevant experience.

Job Duties:

• Designs, configures, develops, tests, and supports informatics and data science solutions for a wide array of technical use cases;
• Collaborate with cross-functional teams, including data scientists and software engineers to integrate AI solutions developed by other elements of CDAO or the DoD community into Search Portfolio products when appropriate.
• Optimize AI models for performance, scalability, and efficiency, leveraging cloud-based resources and distributed computing frameworks, specifically Apache Spark/Databricks. Ability to adapt code base to also run using GPU enabled Kubernetes clusters.
• Stay updated on and contribute to the latest advancements in AI research, applying new findings to improve Search Portfolio products.
• Manage the lifecycle of AI/ML components used in Search Portfolio products from research and development to deployment and optimization.
• Applies analytical methodologies to diagnose data-related challenges, implement solutions, and evaluate performance.
• Documents and presents requirements, design alternatives, and findings to team members and clients.
• Ability to develop strategic, baselined, data modeling processes; ability to accurately determine cause-and-effect relationships.
• Experience with integrated development environments, data integration, data visualization, data mining, and analysis tools.
• Maintains and guides the development of common libraries and tools used by multiple teams.
• Aids in formulating a strategy on how to achieve rapid prototyping.

Required Qualifications:

• Experience with ML fields, e.g., natural language processing, computer vision, statistical learning theory.
• Hands-on experience with Natural Language Processing (NLP), Large Language Models, text embedding, semantic query, use of generative AI for text, and retrieval augmented generation (RAG).
• Familiarity with data preprocessing, feature engineering, and model evaluation techniques essential for machine learning projects.
• Strong understanding of various machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and neural networks.
• Experience with version control systems like Git, enabling effective collaboration and code management.
• Experience in an ML engineer or data scientist role building ML models.
• Experience writing code in Python, R, Scala, Java, C++ with documentation for reproducibility.
• Experience using Apache Spark/Databricks distributed compute environments for AI/ML workloads.
• Experience handling petabyte size datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL, and working with GPUs to develop models.
• Experience with cloud-based data persistence products, especially RDS PostgreSQL and PostgreSQL extensions such as pgvector.
• Experience persisting vectorized data from text embedding processes using Elastic and/or OpenSearch, in addition to vector enabled RDBMS like pgvector enhanced PostgreSQL.
• Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations.
• Possess a minimum of an active Top Secret (TS) security clearance with Sensitive Compartmented Information (SCI) eligibility.

Preferred Qualifications & Skills:

Compensation:

We provide a competitive pay and benefits package. This position is offering a salary range of 165,000-190,000. Belcan considers several factors when extending an offer, including but not limited to education, experience, geographic location, and discipline. Benefits offered may include health care, dental, vision, life insurance; 401(k); education assistance; paid time off including PTO, holidays, and any other paid leave required by law.

Meta Data Scientist – Infrastructure Data Centers

Meta is seeking a highly skilled Data Scientist to lead projects that translate infrastructure data into value. As a lead scientist you will partner with stakeholders, program managers and other data science functions to drive operational efficiency, strategic analysis and machine learning solutions.

$114,000.00/yr – $171,000.00/yr

• Collaborate with cross‑functional teams to define problems, analyze impacts and develop solutions that improve decision‑making and efficiency.
• Translate business challenges into data‑driven problems and design appropriate analytics solutions, including metrics, BI and experimentation.
• Identify operational gaps, build analytical models to derive insights and support decision‑making across leadership.
• Design and implement statistical models such as hypothesis testing, forecasting, process control and simulation to influence critical business decisions and Data Center operations.
• Utilize expertise in statistics, machine learning, optimization and automation to develop analytics solutions.
• Work closely with stakeholders, data engineers, and program/product managers to ensure seamless progress.
• Educate and influence stakeholders to enhance operational efficiency with empathy.
• Recommend process improvements based on operational data and user behavior to boost business performance.

• Bachelor’s degree in Computer Science, Engineering or related field (or equivalent experience) completed prior to joining Meta.
• 4+ years of experience managing and analyzing large‑scale data using Python, R or similar languages.
• 4+ years of experience with visualization tools such as Tableau, PowerBI or similar.
• 4+ years of experience analyzing and interpreting data, developing metrics, drawing conclusions, recommending actions and reporting results across stakeholders.
• 4+ years of experience with advanced SQL in big data environments (e.g., Hive, Presto, Spark) and data modeling.
• Experience enhancing data collection procedures, data processing, cleansing and verifying data integrity.
• Proven track record managing and leading cross‑functional projects and teams.
• Solid understanding of machine learning techniques and algorithms.
• Hands‑on programming experience in AI/ML, LLM, NLP or statistical modeling.
• Proficient in statistical analysis and experimental design.

• Technical knowledge of data center operations.
• Master’s degree in an analytical field (e.g., Operations Research, Statistics).
• Knowledge of simulation and optimization techniques.
• Excellent communication and storytelling skills to influence all organizational levels.

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.

Meta is proud to be an Equal Employment Opportunity and affirmative action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other legally protected characteristics. Meta participates in the E‑Verify program in certain locations, as required by law. Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need assistance or accommodations due to a disability, please let us know at

Overview

Kaiser Aluminum is known around the world for its superior quality. Our secret is what we put into it—innovative thinking, industry-leading reliability, and a world-class commitment to customer service. In short, the same qualities we look for in our people. We are looking for a Data Scientist to join the Kaiser Aluminum onsite team in Spokane Washington!

Must be a USA person (identified as US Citizen, US Permanent Resident (Green Card), any individual who is granted status as a “protected person” under 8 U.S.C. 1324b(a)(3).

• Salary range $85,000 to $125,000 commensurate with experience.
• High deductible medical, dental, vision, and basic life insurance, including spouse and children (modest payroll deductions).
• 10 paid holidays per year.
• Vacation (3 weeks starting out).
• Supplemental leave (used in conjunction with Washington Paid Family & Medical Leave).
• 401K with matching company funds.
• Quarterly bonus structure.
• Tuition reimbursement.

• Conduct the low cost and high quality product and process improvement and optimization through the combination of advanced data analytics and ICME (Integrated Computational Material Science).
• Monitor, evaluate, and apply the advanced computing technologies and algorithms for the most sophisticated data analytics to uncover insights and hidden variables, identify root causes and patterns, forecast outcomes, and provide data-drive solutions.
• Production process data collection, high dimension large dataset multivariate analysis, classic and penalized regression predictive modelling, advanced neural-network and decision-tree based predictive modeling development and applications.
• Develop general and challenge specific predictive modeling capabilities by using commercially available software and/or internal computational codes.
• Design and development of alloys and processes for Aluminum products through advanced data analytics and ICME.
• Provide guidance and mentorship supports for different levels of data analytics including the principle and limits of different analytical algorithms.
• Provide support for Industry 4.0 initiatives.
• Develop, define, and complete on-time assigned research & development chartered projects.
• Support plant projects as directed.
• Write technical reports summarizing work as well as presentations to peers on progress at continuous improvement meetings.
• Perform metallurgical and structural analysis of aluminum products.
• Work in cross-functional teams to develop process and production improvements.
• 5S of assigned areas.

• What you will bring to the role:
• MS degree in Data Science, or Computational Material Science, or Statistics, or Material Science or Mechanical Engineering is required. A PhD is preferred.
• Excellent experience in statistical analysis and computing for data-driven problem solving in manufacturing environment.
• Strong skills and experience in predictive modeling development by using multivariate analysis, classic and penalized regression predictive modelling, advanced neural-network and decision-tree based predictive modeling technologies.
• Experience with the advanced computing technologies and algorithms, such as machine learning, to build high quality predictive modes, uncover insights and hidden variables, and provide solutions.
• Experience in large dataset collection, integration, and visualization by using Excel, SQL, Mintab, Python, etc.
• Background in aluminum manufacturing, physical, and mechanical metallurgy.
• Experience in thermodynamic and kinetic material modeling by using CALPHAD principle, and process simulations by using FEA and CFD tools.
• An ability to apply continuous improvement tools and methodologies to processes and projects
• Excellent communication skills (written and verbal) and organizational skills.
• Proven ability to work in teams.
• Ability to manage multiple tasks simultaneously.

• Experience in metal rolling process simulation through FEA, Crystal Plasticity (CP) model, and other microstructure-based material models.
• Experience in material characterization such as microstructure and mechanical properties.

• Approximately 70% of the job function is performed in an office setting requiring normal safety precautions. 30% of the job function is required in the plant. There is exposure to operating machinery and a manufacturing environment.

We are an equal opportunity employer. All applicants will be considered based on job-related qualifications and abilities. There shall be no discrimination on the basis of age, race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, veteran, or disability status.

About Kaiser Aluminum: Talented people join our team because we are a company passionate about environmental sustainability, employee growth, contributing back to our communities and championing an inclusive culture.

No third-party candidate submissions are being accepted at this time for this opening

Overview

We’re looking for an innovative Data Scientist to join Experian Automotive and shape the future of data-driven decision-making. In this role, you’ll design and implement advanced analytics solutions, standardize and automate data processes, and develop sophisticated statistical, machine learning, and forecasting models that power business intelligence and client insights. You’ll craft next-generation algorithms, build intuitive data visualization tools, and leverage emerging technologies—including generative AI and advanced modeling techniques—to solve high-impact challenges. Collaborating across Finance, Product, Operations, and Technology teams, you’ll drive automation, optimize analytical workflows, and deliver actionable insights that influence strategic decisions. This is an opportunity to push boundaries, transform data into intelligence, and accelerate innovation across the organization.

• Build and optimize scalable data ecosystems to power advanced analytics, predictive modeling, and intelligent decision-making.


• Lead forecasting and scenario modeling by integrating dynamic inputs, validating assumptions, and delivering forward-looking insights that anticipate risks and opportunities.


• Automate and streamline analytical workflows to accelerate speed-to-insight and reduce manual intervention.


• Leverage large-scale structured and unstructured data to uncover patterns, generate actionable insights, and develop predictive and prescriptive models.


• Design, deploy, and operationalize advanced machine learning solutions—including deep learning, graph-based models, and reinforcement learning—to solve complex business and customer challenges.


• Enhance and maintain model development pipelines while driving proof-of-concept initiatives and rapid experimentation.


• Partner with cross-functional teams to define high-impact use cases, align on priorities, and embed data science solutions into strategic decision-making.


• Establish scalable data and model governance practices to ensure reliability, transparency, and continuous improvement.


• Utilize modern analytics and cloud platforms (e.g., Python, AWS, Databricks, Tableau) to deliver cutting-edge solutions.


• Advance algorithmic innovation by refining data analysis techniques, expanding pattern analytics, and generalizing methods for broader data flow coverage.

• Develop intuitive data visualizations and interactive tools to communicate complex insights effectively and drive adoption across the organization.

Experian is the world's leading global information services company, unlocking the power of data to create more opportunities for consumers, businesses and society. We are thrilled to share that FORTUNE has named Experian one of the 100 Best Companies to work for . Also, for the last five years we've been named in the 100 "World's Most Innovative Companies" by Forbes Magazine . With a focus on our employees, we have been certified for the third time as Great Place To Work (GPTW). Experian Consumer Information Services is redefining the way our clients do business within the customer credit lifecycle. Fueled by the best data and technology we help businesses make smarter decisions, identify consumers, make decisions on loans, market to prospects and collect.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.


• Strong proficiency in Python and experience with machine learning frameworks such as scikit-learn, XGBoost, or PyTorch; familiarity with SQL and statistical tools (e.g., R, SAS, MATLAB) is a plus.


• Hands-on experience with generative AI tools, large language models (LLMs), and advanced machine learning techniques including supervised, unsupervised, and time-series modeling.


• Proven ability to deploy and scale models in production using cloud platforms (AWS, GCP, Azure) and tools like Databricks; experience with AWS services such as S3, Redshift, SageMaker, EMR, Kinesis, Lambda, and EC2 is highly desirable.


• Data Mastery: Skilled in analyzing large, complex datasets and developing predictive models, experimental designs, and robust analytic plans to uncover insights and determine causal relationships.


• Statistical Acumen: Deep understanding of statistical modeling, forecasting, and performance optimization for machine learning algorithms.


• Collaboration & Communication: Ability to translate complex technical concepts into clear, actionable insights for diverse stakeholders; strong interpersonal skills for cross-functional collaboration.


• Innovation & Execution: Self-motivated, results-driven professional with a track record of managing projects end-to-end, delivering impactful solutions, and meeting deadlines in fast-paced environments.

Our benefits include: Medical, life and dental insurance, Asociacion Solidarista, International Share Save Plan, Flex Work/Work from home, Paid time off, Annual Performance Bonus, Education Reimbursement, Family Bonding, Bereavement Leave, Referral Program, and more.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is a critical part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

#LI-ML2 #LI-Remote

Overview

We’re looking for an innovative Data Scientist to join Experian Automotive and shape the future of data-driven decision-making. In this role, you’ll design and implement advanced analytics solutions, standardize and automate data processes, and develop sophisticated statistical, machine learning, and forecasting models that power business intelligence and client insights. You’ll craft next-generation algorithms, build intuitive data visualization tools, and leverage emerging technologies—including generative AI and advanced modeling techniques—to solve high-impact challenges. Collaborating across Finance, Product, Operations, and Technology teams, you’ll drive automation, optimize analytical workflows, and deliver actionable insights that influence strategic decisions. This is an opportunity to push boundaries, transform data into intelligence, and accelerate innovation across the organization.

• Build and optimize scalable data ecosystems to power advanced analytics, predictive modeling, and intelligent decision-making.


• Lead forecasting and scenario modeling by integrating dynamic inputs, validating assumptions, and delivering forward-looking insights that anticipate risks and opportunities.


• Automate and streamline analytical workflows to accelerate speed-to-insight and reduce manual intervention.


• Leverage large-scale structured and unstructured data to uncover patterns, generate actionable insights, and develop predictive and prescriptive models.


• Design, deploy, and operationalize advanced machine learning solutions—including deep learning, graph-based models, and reinforcement learning—to solve complex business and customer challenges.


• Enhance and maintain model development pipelines while driving proof-of-concept initiatives and rapid experimentation.


• Partner with cross-functional teams to define high-impact use cases, align on priorities, and embed data science solutions into strategic decision-making.


• Establish scalable data and model governance practices to ensure reliability, transparency, and continuous improvement.


• Utilize modern analytics and cloud platforms (e.g., Python, AWS, Databricks, Tableau) to deliver cutting-edge solutions.


• Advance algorithmic innovation by refining data analysis techniques, expanding pattern analytics, and generalizing methods for broader data flow coverage.

• Develop intuitive data visualizations and interactive tools to communicate complex insights effectively and drive adoption across the organization.

Experian is the world's leading global information services company, unlocking the power of data to create more opportunities for consumers, businesses and society. We are thrilled to share that FORTUNE has named Experian one of the 100 Best Companies to work for . Also, for the last five years we've been named in the 100 "World's Most Innovative Companies" by Forbes Magazine . With a focus on our employees, we have been certified for the third time as Great Place To Work (GPTW). Experian Consumer Information Services is redefining the way our clients do business within the customer credit lifecycle. Fueled by the best data and technology we help businesses make smarter decisions, identify consumers, make decisions on loans, market to prospects and collect.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.


• Strong proficiency in Python and experience with machine learning frameworks such as scikit-learn, XGBoost, or PyTorch; familiarity with SQL and statistical tools (e.g., R, SAS, MATLAB) is a plus.


• Hands-on experience with generative AI tools, large language models (LLMs), and advanced machine learning techniques including supervised, unsupervised, and time-series modeling.


• Proven ability to deploy and scale models in production using cloud platforms (AWS, GCP, Azure) and tools like Databricks; experience with AWS services such as S3, Redshift, SageMaker, EMR, Kinesis, Lambda, and EC2 is highly desirable.


• Data Mastery: Skilled in analyzing large, complex datasets and developing predictive models, experimental designs, and robust analytic plans to uncover insights and determine causal relationships.


• Statistical Acumen: Deep understanding of statistical modeling, forecasting, and performance optimization for machine learning algorithms.


• Collaboration & Communication: Ability to translate complex technical concepts into clear, actionable insights for diverse stakeholders; strong interpersonal skills for cross-functional collaboration.


• Innovation & Execution: Self-motivated, results-driven professional with a track record of managing projects end-to-end, delivering impactful solutions, and meeting deadlines in fast-paced environments.

Our benefits include: Medical, life and dental insurance, Asociacion Solidarista, International Share Save Plan, Flex Work/Work from home, Paid time off, Annual Performance Bonus, Education Reimbursement, Family Bonding, Bereavement Leave, Referral Program, and more.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is a critical part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

#LI-ML2 #LI-Remote