334 Data Scientists jobs in Seattle

Responsibilities

Our team plays a crucial role in the data ecosystem of the TikTok Recommendation System, focusing on creating offline and real-time data storage solutions for large-scale recommendation, search, and advertising businesses, serving over 1 billion users. The core goals of the team are to ensure high system reliability, uninterrupted service, and smooth data processing. We are committed to building a storage and computing infrastructure that can adapt to various data sources and meet diverse storage requirements, ultimately providing efficient, cost-effective, and user-friendly data storage and management tools for the business. Responsibilities 1. Architecture Design and Implementation: Design and implement offline and real-time data architectures for large-scale recommendation, search, and advertising systems based on Paimon and Flink. Ensure efficient data processing and storage to meet the strict requirements of the business for data timeliness and accuracy. 2. System Construction and Optimization: Design and implement flexible, scalable, stable, and high-performance storage systems and computing models. Use Paimon as the storage foundation and combine it with the powerful computing capabilities of Flink. Continuously optimize system performance to cope with the challenges brought by business growth. 3. Troubleshooting and Stability Assurance: Be responsible for troubleshooting production systems. For problems that occur in the Paimon-Flink architecture during operation, design and implement necessary mechanisms and tools, such as data consistency assurance and exception recovery, to ensure the overall stability of the production system. 4. Distributed System Construction: Build industry-leading distributed systems, including offline and online storage based on Paimon and batch and stream processing frameworks based on Flink, providing solid and reliable infrastructure support for massive data and large-scale business systems.

Qualifications

Minimum Qualifications: - A bachelor's degree or above in computer science, software engineering, or related fields, with more than 2 years of experience in building scalable systems. - Technical Skills: 1. Paimon - Flink Technology Stack: Have a thorough understanding of Paimon and Flink, and be able to understand and use them at the source-code level. Experience in customizing or extending these two systems is preferred. 2. Data Lake Technology: Have an in-depth understanding of at least one data lake technology (such as Paimon), with practical implementation and customization experience, which should be highlighted in the resume. 3. Storage Knowledge: Be familiar with the principles of HDFS, and knowledge of columnar storage formats such as Parquet and ORC is preferred. 4. Programming Languages: Be proficient in programming languages such as Java, C++, and Scala, with strong coding and problem-solving abilities. - Project Experience: Have experience in data warehouse modeling and be able to design efficient data models that meet complex business scenarios. - Experience in using other big-data systems/frameworks (such as Hive, HBase, Kudu, etc.) is preferred. - Comprehensive Qualities: Have the courage to take on complex problems and be willing to explore problems without clear solutions. - Be passionate about learning new technologies and be able to quickly master and apply them to practical work. - Experience in handling large-scale data (PB - level and above) is preferred.

Job Information

(For Pay Transparency)Compensation Description (Annually)

The base salary range for this position in the selected city is $ - $ annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.

We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

TikTok Accommodation

TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at

• Lead the design, development, and implementation of advanced machine learning models and algorithms to solve complex business problems.
• Conduct exploratory data analysis, feature engineering, and model selection to optimize predictive accuracy and performance.
• Develop and deploy ML models into production environments, ensuring scalability, robustness, and maintainability.
• Stay abreast of the latest research and advancements in machine learning, artificial intelligence, and related fields, and identify opportunities for application.
• Mentor and guide junior data scientists and engineers, fostering technical excellence and knowledge sharing.
• Collaborate with product managers, engineers, and business stakeholders to define project requirements and translate them into data science solutions.
• Communicate complex findings and recommendations clearly and concisely to both technical and non-technical audiences.
• Evaluate and select appropriate tools, technologies, and frameworks for data science projects.
• Contribute to the development of the company's data science strategy and long-term vision.
• Design and conduct experiments to validate hypotheses and measure the impact of ML solutions.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• 8+ years of experience in data science, with a strong focus on machine learning model development and deployment.
• Proven track record of delivering impactful ML solutions in production environments.
• Expertise in a wide range of ML algorithms, including supervised, unsupervised, and deep learning techniques.
• Proficiency in programming languages such as Python (with libraries like TensorFlow, PyTorch, scikit-learn) and R.
• Strong experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP).
• Excellent understanding of statistical modeling, experimental design, and data mining techniques.
• Exceptional problem-solving skills and the ability to think critically and creatively.
• Outstanding communication and presentation skills, with the ability to explain complex technical concepts to diverse audiences.
• Demonstrated leadership capabilities and experience mentoring technical teams.

• Design, develop, and implement advanced machine learning models and algorithms.
• Perform exploratory data analysis and feature engineering on large datasets.
• Evaluate and optimize model performance using rigorous statistical methods.
• Deploy machine learning models into production environments.
• Collaborate with cross-functional teams to define business problems and translate them into data science solutions.
• Communicate complex findings and insights to technical and non-technical stakeholders.
• Stay current with the latest advancements in machine learning, AI, and data science.
• Mentor junior data scientists and contribute to the team's knowledge base.
• Develop and maintain robust data pipelines and workflows.
• Conduct A/B testing and other experiments to validate model effectiveness.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of professional experience in data science and machine learning.
• Proven expertise in developing and deploying machine learning models for various applications (e.g., prediction, classification, recommendation systems, NLP).
• Proficiency in programming languages such as Python or R and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Keras).
• Experience with big data technologies (e.g., Spark, Hadoop) and SQL.
• Familiarity with cloud computing platforms (AWS, Azure, GCP) and their data science services.
• Strong understanding of statistical concepts, experimental design, and data mining.
• Excellent problem-solving, analytical, and critical thinking skills.
• Effective communication and presentation skills.

• Designing, developing, and implementing sophisticated machine learning algorithms and statistical models to address business needs, such as predictive analytics, recommendation systems, natural language processing, and computer vision.
• Performing extensive data exploration, cleaning, and feature engineering on large, complex datasets from various sources.
• Collaborating closely with product managers, engineers, and other data scientists to define project scope, establish key performance indicators (KPIs), and deliver impactful solutions.
• Conducting rigorous model evaluation, validation, and A/B testing to ensure accuracy, reliability, and scalability.
• Translating complex analytical findings and model results into clear, concise, and actionable recommendations for technical and non-technical stakeholders through compelling visualizations and presentations.
• Staying abreast of the latest advancements in machine learning, deep learning, and artificial intelligence, and exploring their potential applications within the company.
• Contributing to the development and maintenance of our data science infrastructure, tools, and best practices.
• Mentoring junior data scientists and fostering a collaborative learning environment.
• Proactively identifying opportunities to leverage data science to improve business outcomes.

• Design, develop, and implement sophisticated machine learning models for a wide range of applications, including but not limited to natural language processing, computer vision, recommendation systems, and predictive analytics.
• Conduct in-depth data analysis, feature engineering, and model validation to ensure accuracy and performance.
• Collaborate with cross-functional teams, including product managers, engineers, and business analysts, to understand requirements and translate them into data-driven solutions.
• Stay at the forefront of ML research and techniques, exploring and applying novel algorithms and methodologies.
• Develop and maintain robust data pipelines and infrastructure for training and deploying ML models.
• Optimize model performance for scalability, efficiency, and real-time application.
• Communicate complex technical findings and insights clearly and effectively to both technical and non-technical audiences.
• Contribute to the development of best practices and standards for machine learning development within the organization.
• Mentor junior data scientists and share knowledge across the team.
• Evaluate and integrate new tools and technologies to enhance the ML development workflow.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• 5+ years of experience in advanced data science and machine learning, with a strong portfolio of deployed ML models.
• Expertise in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Keras).
• Proficiency in SQL and experience with big data technologies (e.g., Spark, Hadoop).
• Deep understanding of statistical modeling, algorithm development, and data mining techniques.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps principles is highly desirable.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills, with the ability to work effectively in a remote, team-oriented environment.
• Published research in top-tier ML conferences or journals is a significant plus.
• Passion for innovation and a drive to solve challenging real-world problems using data.