61,355 IT Data jobs in the United States

• Design, build, and maintain scalable data science workflows and GenAI/ML pipelines using Databricks, SQL, Python, and cloud-native tools.
• Develop and deploy LLM-powered agents and GenAI solutions that automate insights, optimize customer journeys, and surface proactive recommendations.
• Create and evolve models that predict customer health, churn risk, and value realization, integrating them into robust internal tools and dashboards.
• Collaborate with partners across ACS and DX to understand business needs and translate them into actionable data products.
• Conduct ad hoc and deep-dive analyses to uncover trends, anomalies, and opportunities in customer behavior and engagement.
• Evaluate, fine-tune, and maintain LLMs and ML models using platforms like Azure OpenAI, AWS Claude, and Google Gemini.
• Contribute to the architecture and evolution of our internal analytics ecosystem, ensuring reliability, performance, and scalability.
• Use Git, Databricks Repos, and CI/CD best practices to ensure reproducibility and collaboration.
• Continuously explore and prototype new tools, frameworks, and AI capabilities to keep our solutions on the cutting edge.

• Bachelor's or graduate degree in Computer Science, Data Science, Engineering, or a related field.
• 8+ years of experience in data engineering, data science, ML engineering roles, or relevant experience.
• Strong proficiency in Python, SQL, and distributed computing frameworks like Spark.
• Hands-on experience with Databricks, Delta Lake, and cloud platforms (Azure, AWS, or GCP).
• Deep understanding of LLMs, agentic workflows, and GenAI tools (e.g., Copilot, Claude, Gemini, LLaMA, Databricks Genie).
• Proven track record of building and deploying ML models in production environments.
• Experience with model evaluation, tuning, and lifecycle management (e.g., MLflow).
• Familiarity with Adobe's DX ecosystem is a plus (e.g., Adobe Experience Platform, Adobe Analytics, Customer Journey Analytics).
• Excellent communication and collaboration skills, with the ability to work across technical and non-technical teams.
• A passion for innovation, experimentation, and building tools that make a real impact.
• Innovative thinking, perseverance, and an ability to deal with complex problems
• Demonstrated ability to work independently, navigate ambiguity, and deliver outcomes that will improve current states and business outcomes.

• Experience with data visualization tools (e.g., Power BI, Tableau, Adobe Workspace).
• Familiarity with orchestration tools like Airflow or Databricks Workflows.
• Exposure to graph databases, Elastic Stack, or real-time streaming (Kafka, Kinesis).
• Contributions to open-source projects or a strong portfolio of personal projects.

Job Description

Summary:
We are seeking a Data Analyst to support Global Tech Business Operations and Enablement analytics by developing automated auditing platforms and delivering scalable data solutions. This role will focus on Python and SQL-based data engineering, reporting, and visualization, while also driving process improvements and cross-functional collaboration. The ideal candidate will combine strong technical expertise with analytical problem-solving, communication skills, and the ability to work in a fast-paced global environment.

Position Info:

• Title : Data Science Engineer

• Client : Nike

• Duration : 12-month contract w/ possible extensions

• Location : Beaverton, Oregon

• Work Mode : Hybrid

Responsibilities:

• Develop and maintain automated auditing platforms for labor and finance data using Python and SQL

• Partner with stakeholders to gather requirements, build sustainable data solutions, and deliver insights

• Validate KPIs, build queries, and perform advanced statistical analysis and data mining

• Create SQL-based reports and Tableau/Power BI visualizations for ongoing reporting and ad-hoc requests

• Establish data governance standards and ensure data quality from ingestion through reporting

• Improve existing workflows through automation and scalable processes

• Communicate complex technical solutions in clear, business-relevant language

• Support product strategy, reporting decisions, and enterprise analytics initiatives

Skills/Qualifications:

• 1–4 years of relevant work experience in data analytics or engineering

• Proficiency in Python, SQL, or R for data processing and automation

• Strong knowledge of Excel, data cleansing, and statistical modeling

• Experience with Tableau or Power BI for data visualization

• Familiarity with machine learning algorithms and advanced analytics techniques

• Strong analytical mindset with excellent attention to detail and problem-solving skills

• Excellent communication skills with ability to work across global, cross-functional teams

• Project management experience with ability to handle ambiguity and fast-paced environments

Nice to Have:

• Experience with AWS RDS, MySQL, or Databricks

• Knowledge of data ingestion pipelines and GitHub/CoPilot

• Familiarity with Confluence, Jira, and enterprise matrix structures

• Experience creating professional presentations in PowerPoint

Company Description

Ohm Systems, Inc. specializes in IT and Healthcare staffing services, dedicated to linking highly skilled professionals with our public and private clients across the United States. Our track record showcases our commitment to delivering outstanding staffing and consultancy solutions to our clients. We prioritize diversity and inclusivity and take pride in being an employer that promotes equal opportunities and affirmative action. Our goal is to foster an inclusive work environment that embraces individuals from all backgrounds, irrespective of their gender, race, or orientation.

Ohm Systems, Inc. specializes in IT and Healthcare staffing services, dedicated to linking highly skilled professionals with our public and private clients across the United States. Our track record showcases our commitment to delivering outstanding staffing and consultancy solutions to our clients. We prioritize diversity and inclusivity and take pride in being an employer that promotes equal opportunities and affirmative action. Our goal is to foster an inclusive work environment that embraces individuals from all backgrounds, irrespective of their gender, race, or orientation.

Must have Skills : Python for Data Science (Strong), Prompt Engineering, knowledge graph, Good To Have Skills : AWS,

Job Description : Overall 7-10 years of experience in Data Science with LLM experience as must - 2+ years of experience developing and experimenting with LLMs

- 6+years of experience developing AI/Client technologies within large and business critical applications

- Proficiency in Python and all associated DS libraries and frameworks

- Strong knowledge in AI, machine learning, and natural language processing

- Experience with leveraging, training and fine-tuning Foundation Models, including multimodal inputs and outputs

- Strong experience working with key LLM models APIs (e.g. OpenAI, Anthropic) and LLM Frameworks (e.g. LangChain, LlamaIndex)

- Experience with multi-agent frameworks/systems and an understanding of multi-agent systems and their applications in complex problem

-solving scenarios.

- Experience with unstructured.io or similar libraries for handling various document formats and extracting structured information from unstructured data.

- Expertise in using LlamaIndex for building and querying knowledge bases, including its data connectors, indexing strategies, and query engines.

- Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets.

- Proficiency in generating and working with text embeddings using models like BERT, GPT, or domain-specific embedding models. Understanding of embedding spaces and their applications in semantic search and information retrieval.

- Experience in constructing and querying knowledge graphs, including technologies like Neo4j or RDF triplestores. Understanding of ontology design and graph-based reasoning.

- Experience with RAG concepts and fundamentals (vectorDBs, semantic search, etc.), Expertise in implementing RAG systems that combine knowledge bases with generative AI models.

Hi Professionals,
Hope you are doing good

This is Jayaraman from Info Way Solutions, LLC We have job opening for Data Science Engineer and the detailed Job description is given below:

Kindly check the JD and share your views
Data Science Engineer
Job Location: Boston, MA - 4 days to office.
( Local Profile only )

Job Description:
We are seeking a talented Data Science Engineer to join our team and contribute to the development and implementation of advanced data solutions using technologies such as AWS Glue, Python, Spark, Snowflake Data Lake, S3, SageMaker, and machine learning (M/L).
As a Data Science Engineer, you will play a crucial role in designing, building, and optimizing data pipelines, machine learning models, and analytics solutions. You will work closely with cross-functional teams to extract actionable insights from data and drive business outcomes.
Key Responsibilities:
• Develop and maintain ETL pipelines using AWS Glue for data ingestion, transformation, and integration from various sources.
• Utilize Python and Spark for data preprocessing, feature engineering, and model development.
• Design and implement data lake architecture using Snowflake Data Lake, Snowflake data warehouse and S3 for scalable and efficient storage and processing of structured and unstructured data.
• Leverage SageMaker for model training, evaluation, deployment, and monitoring in production environments.
• Collaborate with data scientists, analysts, and business stakeholders to understand requirements, develop predictive models, and generate actionable insights.
• Conduct exploratory data analysis (EDA) and data visualization to communicate findings and trends effectively.
• Stay updated with advancements in machine learning algorithms, techniques, and best practices to enhance model performance and accuracy.
• Ensure data quality, integrity, and security throughout the data lifecycle by implementing robust data governance and compliance measures.

Qualifications:
• Bachelor's degree or higher in Computer Science, Data Science, Statistics, or related field.
• Proficiency in AWS services such as Glue, S3, SageMaker, and Snowflake Data Lake with 5-6 years of experience.
• Strong programming skills in Python for data manipulation, analysis, and modeling.
• Experience with distributed computing frameworks like Spark for big data processing.
• Knowledge of machine learning concepts, algorithms, and tools for regression, classification, clustering, and recommendation systems.
• Familiarity with data visualization tools with Tableau for creating meaningful visualizations.
• Excellent problem-solving, analytical thinking, and communication skills.
• bility to work collaboratively in a team environment and manage multiple priorities effectively.
• Experience deploying machine-learning models in production environments and monitoring their performance.
• Knowledge of MLOps practices, model versioning, and automated model deployment pipelines.
• Familiarity with SQL, NoSQL databases, and data warehousing concepts.
• Strong understanding of cloud computing principles and architectures.
• Certifications in AWS, Python, Spark, or related technologies.

Thanks & Regards,
Jayaraman
Email:
Direct: (
Work: ( Ext 105
Info Way Solutions LLC | 46520 Fremont Blvd, Suite 614 | Fremont, CA - 94538

Job Title: Data Science Engineer

Location: Boston, MA - 4 days to office.

Job Description:
We are seeking a talented Data Science Engineer to join our team and contribute to the development and implementation of advanced data solutions using technologies such as AWS Glue, Python, Spark, Snowflake Data Lake, S3, SageMaker, and machine learning (M/L).
As a Data Science Engineer, you will play a crucial role in designing, building, and optimizing data pipelines, machine learning models, and analytics solutions. You will work closely with cross-functional teams to extract actionable insights from data and drive business outcomes.
Key Responsibilities:

• Develop and maintain ETL pipelines using AWS Glue for data ingestion, transformation, and integration from various sources.
• Utilize Python and Spark for data preprocessing, feature engineering, and model development.
• Design and implement data lake architecture using Snowflake Data Lake, Snowflake data warehouse and S3 for scalable and efficient storage and processing of structured and unstructured data.
• Leverage SageMaker for model training, evaluation, deployment, and monitoring in production environments.
• Collaborate with data scientists, analysts, and business stakeholders to understand requirements, develop predictive models, and generate actionable insights.
• Conduct exploratory data analysis (EDA) and data visualization to communicate findings and trends effectively.
• Stay updated with advancements in machine learning algorithms, techniques, and best practices to enhance model performance and accuracy.
• Ensure data quality, integrity, and security throughout the data lifecycle by implementing robust data governance and compliance measures.

• Bachelor's degree or higher in Computer Science, Data Science, Statistics, or related field.
• Proficiency in AWS services such as Glue, S3, SageMaker, and Snowflake Data Lake with 5-6 years of experience.
• Strong programming skills in Python for data manipulation, analysis, and modeling.
• Experience with distributed computing frameworks like Spark for big data processing.
• Knowledge of machine learning concepts, algorithms, and tools for regression, classification, clustering, and recommendation systems.
• Familiarity with data visualization tools with Tableau for creating meaningful visualizations.
• Excellent problem-solving, analytical thinking, and communication skills.
• Ability to work collaboratively in a team environment and manage multiple priorities effectively.
• Experience deploying machine-learning models in production environments and monitoring their performance.
• Knowledge of MLOps practices, model versioning, and automated model deployment pipelines.
• Familiarity with SQL, NoSQL databases, and data warehousing concepts.
• Strong understanding of cloud computing principles and architectures.
• Certifications in AWS, Python, Spark, or related technologies.

Job Title : Data Science Engineer Experience Required - 4+ Years

Must Have Technical/Functional Skills
• Proficiency in Python or R for data analysis and modeling.
• Experience of reading through code repos to understand logic.
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau, Power BI).
• Experience building GenAI chatbots, implementing tools with Gemini or similar vendors.
• Ability to work with LLM APIs.
• Knowledge in prompt engineering.
• Knowledge in RAG architecture.
• Knowledge in Google Cloud and Vertex AI.
• Familiarity with Agile methodologies and project management tools (e.g., Jira,Github).
• Excellent communication skills (both verbal and written).
• Must be self-motivated and know when to seek guidance.
• Capable of learning new tools and technologies.

Salary Range - $85,000 to $105,000 per year

• Develop and own rSAM models to size headroom opportunities in the book of business for specific offerings and customer segments
• Carry out in-depth business analysis to uncover the drivers behind performance gaps and make recommendations for change
• Engage with senior collaborators to understand key growth areas and ensure solutions align with business priorities
• Assess and improve the performance of sales campaigns with performance insights and recommendations for model enhancements
• Support the customer segmentation process using rSAM and other insights
• Provide different models like customer segmentation based on clustering, customer lifetime value based on survival analysis, and forecasting
• Deliver channel segmentation to determine customer engagement strategy and optimize lifetime value
• Collaborate with data engineering teams to productionize data pipelines and drive scalable solutions
• Automate model refreshes and account prioritization processes
• Build propensity models to drive sales campaigns using predictive modelling techniques

• 5+ years of SQL experience for querying, cleansing, integrating, and summarizing complex data is essential
• Experience with Databricks and Python is desirable
• Proven experience of building, testing, evaluating, and improving revenue-generating data science models
• Knowledge of propensity modeling techniques and other modeling techniques would be beneficial
• Proven experience translating complex analytics into understandable insights for senior collaborators is essential
• Strong problem-solving skills and experience in a fast-paced business environment with changing requirements

• 7+ years of data science, machine learning, advanced analytics experience
• Experience deploying Data Science / Client solutions in production for achieving results.
• Coding skills in Python and SQL
• Experience with distributed data processing systems like Spark and familiarity with software engineering principles around testing, code reviews and deployment.
• Experience with Databricks
• Conversant in Natural Language (NL Model).
• Deep understanding of LLM models.
• Data analysis skills.
• Gen AI interactive skills.