This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Staff Data Scientist on the Decision Science team at PlayStation, you will take a leading role in designing and interpreting experiments that evaluate the impact of key initiatives and programs. You’ll help shape how millions of players around the world experience PlayStation by bringing statistical rigor, clear measurement strategies, and deep causal inference expertise to some of the most critical initiatives across the company. This highly visible role will advance our experimentation practices and ensure that data-driven insights inform the way we build, market, and evolve our products. What You’ll Be Doing: - Design, execute, and interpret A/B tests and quasi-experiments, and apply advanced causal inference methods when experimentation isn’t feasible. - Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles and communicate results with the company’s senior leadership. - Mentor and guide other Data Scientists, providing thought leadership and technical direction. - Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results communication. - Help define and contribute to centralized experimentation frameworks, tools, and documentation to scale best practices across the company. - Independently extract, transform, and analyze data from complex systems using SQL, Python, and other analytics tools. - Communicate findings clearly to technical and non-technical stakeholders, helping drive business decisions with rigor and clarity. - Stay current on new methodologies in experimentation and causal analysis, and bring fresh perspectives to the team’s work. - Your insights will directly influence how PlayStation builds, markets, and evolves products across our ecosystem. Qualifications - Master’s or PhD in Statistics, Economics, or Econometrics. - 6+ years of experience in a data science experimentation/causal inference-focused role (4+ with PhD). - Deep expertise in A/B testing and causal inference, including quasi-experimental methods. - Proficiency in SQL and Python for data extraction, transformation, and analysis. - Broad and applied knowledge of statistical techniques. - Experience with machine learning modeling is a plus. - Proven ability to influence product and business decisions through clear, actionable insights. - Experience contributing to or developing experimentation frameworks, best practices, or internal tooling. - Bonus: Passion for video games, player communities, or the gaming industry. Requirements - Master’s or PhD in Statistics, Economics, or Econometrics. - 6+ years of experience in a data science experimentation/causal inference-focused role (4+ with PhD). - Deep expertise in A/B testing and causal inference, including quasi-experimental methods. - Proficiency in SQL and Python for data extraction, transformation, and analysis. - Broad and applied knowledge of statistical techniques. - Experience with machine learning modeling is a plus. - Proven ability to influence product and business decisions through clear, actionable insights. - Experience contributing to or developing experimentation frameworks, best practices, or internal tooling. - Bonus: Passion for video games, player communities, or the gaming industry. Benefits - Medical, dental, and vision coverage. - Matching 401(k) plan. - Paid time off. - Wellness program. - Employee discounts for Sony products. - Potential eligibility for a bonus package.

Role Description Supports U.S. Customs and Border Protection. As a Data Scientist, with little or no supervision, apply expert knowledge in statistical analysis, complex data mining, and artificial intelligence to make value out of data. Provide consulting relating to the data mining and analysis of data from a range of sources to transform raw data into concise and actionable insights. Design and implement data-driven solutions, with specific focus on advanced analytical methods, data models, and visualizations. Develop quantitative simulations and models to provide descriptive and predictive analytics solution recommendations. Identify trends and problems through complex big data analysis. Maintain current in emerging tools and techniques in machine learning, statistical modeling, and analytics. Qualifications - Six (6) years of relevant experience in applied research, big data analytics, statistics, applied mathematics, data science, computer science, operations research or other closely related quantitative or mathematical discipline. - At least three (3) years of direct experience in machine learning. - Advanced Degree (Masters or PhD) in Statistics, Applied Mathematics, Data Science, Computer Science, Operations Research or other closely related quantitative or mathematical discipline. A PhD degree may be substituted for up to three (3) years of relevant experience. - Demonstrates knowledge of data mining methods, databases, data visualization and machine learning. - Ability to communicate analysis techniques, concepts and products. - Ability to develop data-driven solutions, data models, and visualizations. Requirements - Expertise using Qlik to embed visualizations into webpages. - Familiarity with Databricks or similar cloud-based distributed database technologies. - Familiarity with PySpark and Python. - Comfortable developing complex SQL queries to extract, transform, and load data. - Experience with analytic techniques such as Anomaly detection, Clustering, and Time-series (e.g., ARIMA). - Experience implementing NLP concepts including preprocessing (stemming, etc.), TF-IDF, Named Entity Recognition, and LLMs. Benefits - Competitive Salary and Benefits. - Important Work / Make a Difference: supporting Customs and Border Protection in their efforts to protect the United States. - Job Stability: Elder Research is not a typical government contractor, we hire you for a career not just a contract. - Remote Work: in an industry of declining remote work opportunities. - People-Focused Culture: we prioritize work-life balance and provide a positive, supportive work environment as well as opportunities for professional growth and advancement. - Company Stock Ownership: all employees are provided with shares of the company each year based on company value and profits.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We're looking for an accomplished Data Science Manager to lead our data science team in delivering high-impact analytics and machine learning solutions across the business. You'll oversee a high performing team driving predictive modeling, customer insights, operational optimization, and product innovation using our rich datasets on Google Cloud Platform (GCP). Reporting directly to the VP of Data, you'll partner closely with product, engineering, and business leaders to translate data into actionable strategies. This role emphasizes strong people leadership, agile delivery, and the ability to communicate complex insights simply to non-technical executives. Experience with geospatial data is a plus but not required—we value broad data science expertise on modern cloud infrastructure. As an onX Data Science Manager, your essential job duties and responsibilities will look like: - Lead and mentor a team of 3 data scientists and ML engineers, focusing on technical guidance, career growth, and performance management. - Define and prioritize the data science roadmap, aligning projects with company goals across customer behavior modeling, forecasting, recommendation systems, and operational efficiency. - Oversee the design, development, and production deployment of advanced machine learning models and analytical solutions at scale. - Partner with stakeholders across product, engineering, and business teams to identify high-value opportunities and deliver measurable impact through data. - Promote best practices in data governance, model validation, and MLOps on GCP to ensure reliable, scalable solutions. - Drive agile ways of working: backlog refinement, sprint planning, and rapid iteration to accelerate business value. - Present insights and recommendations to executive leadership through clear storytelling, visualizations, and executive-friendly summaries. - Keep the team up to date on GCP innovations (e.g., Vertex AI, BigQuery ML) and emerging data science trends. Qualifications - 8+ years in data science, machine learning, or advanced analytics, with at least 3 years managing technical teams. - Proven track record of delivering business impact through data science in a product-driven tech environment. - Hands-on expertise with GCP data and ML services: BigQuery, Vertex AI, Dataflow, BigQuery ML, and related tools. - Strong proficiency in Python, Spark, SQL, and common data science libraries (pandas, scikit-learn, TensorFlow/PyTorch, etc.). - Demonstrated ability to explain technical concepts and results clearly to non-technical audiences. - Experience operating in agile environments with cross-functional collaboration. Requirements - Advanced degree (MS/PhD) in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field (preferred but not required). - Familiarity with Master Data Management principles to maintain high-quality, governed reference data (preferred but not required). - Exposure to geospatial tools (e.g., BigQuery GIS) or location-based analytics (preferred but not required). - Experience building and scaling cloud-native MLOps pipelines (preferred but not required). Benefits - Competitive salaries, annual bonuses, equity, and opportunities for growth. - Comprehensive health benefits including a no-monthly-cost medical plan. - Parental leave plan of 5 or 13 weeks fully paid. - 401k matching at 100% for the first 3% you save and 50% from 3-5%. - Company-wide outdoor adventures and amazing outdoor industry perks. - Annual “Get Out, Get Active” funds to fuel your active lifestyle in and outside of the gym. - Flexible time away package that includes PTO, STO, VTO, and Holidays.

• Partner closely with Product Managers to influence roadmaps using product insights • Be opinionated about what signals matter most at different stages of the product lifecycle • Define and evolve core product metrics related to adoption, engagement, and long-term value to support product decisions • Analyze product usage to identify opportunities to improve the developer experience • Frame success criteria and trade-offs to support product prioritization • Design analyses and experiments to inform product investments • Communicate insights clearly to senior stakeholders across Platform • Contribute to a culture of learning, collaboration, and thoughtful use of data