Data Instructor Jobs

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re hiring a Data Scientist to help build and scale our internal analytics capabilities. This is a foundational role where you’ll create dashboards, models and insights to power business and product teams alike. You’ll collect requirements, define key metrics, and deliver recommendations directly to stakeholders. You'll define what success looks like across a technical, usage-based platform and turn ambiguous questions into analyses, forecasts, and experiments that shape Baseten’s product and strategy. RESPONSIBILITIES Build and maintain production-grade models and dashboards across multiple functions with a focus on accuracy, simplicity and user experience. Define and instrument core metrics around capacity, availability, ROI, product adoption, revenue and costs. Ingest and transform raw data using tools like dbt, Airbyte, and Databricks. Partner with Engineering, Finance, Marketing, and Sales teams to understand goals and translate them into data solutions Analyze product, operational and commercial data to identify opportunities, quantify tradeoffs, and influence product and GTM priorities. Present findings and recommendations to technical and nontechnical audiences, including company leaders. REQUIREMENTS 5+ years of experience in analytics, BI, or data engineering roles Strong SQL skills with the ability to write complex queries for data transformation and analysis Experience designing medallion data arch

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re hiring a Data Scientist to help build and scale our internal analytics capabilities. This is a foundational role where you’ll create dashboards, models and insights to power business and product teams alike. You’ll collect requirements, define key metrics, and deliver recommendations directly to stakeholders. You'll define what success looks like across a technical, usage-based platform and turn ambiguous questions into analyses, forecasts, and experiments that shape Baseten’s product and strategy. RESPONSIBILITIES Build and maintain production-grade models and dashboards across multiple functions with a focus on accuracy, simplicity and user experience. Define and instrument core metrics around capacity, availability, ROI, product adoption, revenue and costs. Ingest and transform raw data using tools like dbt, Airbyte, and Databricks. Partner with Engineering, Finance, Marketing, and Sales teams to understand goals and translate them into data solutions Analyze product, operational and commercial data to identify opportunities, quantify tradeoffs, and influence product and GTM priorities. Present findings and recommendations to technical and nontechnical audiences, including company leaders. REQUIREMENTS 5+ years of experience in analytics, BI, or data engineering roles Strong SQL skills with the ability to write complex queries for data transformation and analysis Experience designing medallion data arch

Scale's Data Analytics team is centralized, embedding data analysts across delivery, operations, finance, and engineering to turn ambiguous problems into clear, actionable insights. As a Senior Data Analyst for Public Sector, you'll build analytics solutions from the ground up - partnering closely with cross-functional teams and leadership to solve complex problems, design dashboards, build tables, and perform ad-hoc analyses that shape how Scale runs and measures its Public Sector business. We're looking for someone who's relentlessly curious, comfortable owning ambiguity, and skilled at turning cross-functional relationships into sustainable, scalable analytics solutions. Active Secret U.S. security clearance required You will: Own data quality for your domain - document models, troubleshoot discrepancies, and establish centralized metric definitions Collaborate with cross-functional teams to identify, define, and track key metrics to be used in monitoring, planning, and one-off decision-making Develop repeatable, scalable analytical solutions, such as dashboards, data models, or standard processes Partner with Ops to identify and track efficiency initiatives, measuring their impact on cost, quality, and delivery outcomes over time Partner with Finance to analyze cost drivers across programs and help inform pricing strategy Be willing to deepdive when needed and dig into the messy details to get to the root of a problem Initiate and drive complex projects to completion with minimal guidance Ideally you'd have: 6+ years of relevant work experience Advanced SQL skills and experience building with data modeling tools (e.g. DBT) Experience building dashboards and reports with BI tools (e.g. Tableau, Metabase) Strong business acumen - comfortable partnering directly with cross-functional stakeholders Excellent communication skills - able to translate technical analysis into clear, actionable narratives Comfort with ambiguity in a fast-moving environment and able

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We’re looking for a principal software engineer to lead the next generation of data infrastructure at Pinterest which powers mission critical big data and AI applications. You’ll be working on some of the most exciting big data and AI open source technologies (Flink, Spark, Kubernetes, etc.), at the scale of exabytes of data to help Pinners discover and do what they love. What you’ll do: Lead the strategy and technical direction of Pinterest’s data infrastructure for big data and AI applications Build and scale data infra frameworks and infrastructure to process petabytes-scale datasets, including compute engines, job management, resource management, scheduling and remote shuffling Work with internal customers on critical business use cases that rely on big data Provide thought leadership to the entire company on how data should be

This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Senior Data Engineer - Payments At Adyen, we treat data and data artifacts as first-class citizens. In this role, you'll be at the core of our data strategy by helping us in building the best-in-class data platform for payments, and creating meaningful data products that drive our external and internal stakeholders. You'll also work in creating and maintaining robust reporting solutions that provide concise, reliable, and trustworthy intelligence to our customers. What you’ll do Collaborative Solution Development : Engage with a diverse range of stakeholders, including data scientists, analysts, software engineers, product managers, and customers, to understand their requirements and craft effective solutions. State-of-the-Art Pipelines and Architecture : Design, develop, deploy and operate high-quality production ELT pipelines and data architectures. Integrate data from various sources and formats, ensuring compatibility, consistency, and reliability. Design scalable architectures. Champion Data Best Practices : Proactively establish and advocate for best practices in performance, code quality, data validation, data governance, and discoverability across Adyen through mentoring, training, and knowledge sharing. High Quality Data and Code: Ensure data is accurate, complete, reliable, relevant, and timely. Implement rigorous te

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Responsibilities: Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context. Perform exploratory data analysis to gain a deeper understanding of the problem. Construct and fit statistical, machine learning, or optimization models. Write production modeling code. Collaborate with Software Engineers to implement algorithms in production. Design and run both simulated and live traffic experiments. Analyze experimental and observational data. Communicate findings. Facilitate launch decisions. Experience: Master’s degree or foreign equivalent in Mathematics, Statistics, Economics, or related field. 2 years of experience in job offered, Operations Research, or related occupation. Experience with solving unstructured and non-standard mathematical problems. Experience with end-to-end data including querying, aggregation, analysis, and visualization. Experience with Python and other programming languages such as R and MATLAB. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible Subsidized commuter benefits Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As a Data Scientist on the Mapping team, you will collaborate with our world class team of scientists, engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our geospatial, behavioural and mobility data, and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers. Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. The Mapping team serves models and systems that determine the most efficient routes, fastest travel estimates and process real-time map data signals to detect traffic, closures and slowdowns. Working with our business and analytics partners, the team owns tools to ensure Lyft offers routes that our users trust. This will involve identifying and scoping opportunities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in Mapping, including: How do we accurately predict acute and chronic traffic conditions? How do we improve the recommendations of our routing algorithms? How do we keep our travel estimation promises to our riders and drivers? How do we benchmark and measure the success of our services? Responsibilities: Own the complete lifecycle of algorithmic solutions from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration Prioritize and lead deep dives into our data to uncover new product and business opportunities Partner closely with E

About the Team At Trendyol Tech, our mission is to create a positive impact in our ecosystem by enabling commerce through technology. We solve complex problems with data, creativity, and agility — always driven by real outcomes. With a culture built on learning, collaboration, and ownership, we grow together while building what’s next. About the Role Our team builds the language intelligence and retrieval foundations behind Trendyol Search across multiple regions. We focus on helping customers express their intent accurately and discover relevant products quickly, regardless of the language or market they search in. As a Data Scientist, you will work on high-impact problems at the intersection of NLP, information retrieval, and e-commerce search. You will contribute to multi-regional search models covering spelling correction, query understanding, semantic and vector search, while taking particular ownership in improving the Arabic-language search experience. Your work will directly improve product discovery for millions of customers across Trendyol's markets. Responsibilities Develop and improve query understanding capabilities for Trendyol's search experience across multiple regions and languages, including spelling correction, query normalization, query rewriting, intent detection, and semantic retrieval. Build and evaluate vector search, embedding, and retrieval models that improve the relevance of product discovery for customers across different markets. Take a leading role in Arabic-language search initiatives, addressing language-specific challenges such as dialectal variation, orthographic normalization, transliteration, morphology, mixed-language queries, and spelling errors. Analyze large-scale structured and unstructured data, including search queries, product content, user interactions, and linguistic signals across the Trendyol ecosystem. Design robust offline evaluation methodologies and quality metrics for

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: The Data Engineer is responsible for the design, development, and implementation of scalable data solutions across the Azure Databricks platform supporting AUNZ. This role focuses on building and maintaining data pipelines using Databricks (Unity Catalog, DABs, DLT), PySpark, and SQL, delivering enterprise-scale data transformation, and supporting Power BI reporting through well-modelled silver/gold layer datasets. The Data Engineer works closely with the Head of Data & Analytics to execute technical scoping and delivery against business requirements. What you'll be doing: KRA 1 Data Pipeline Development • Design, build, test, and maintain data pipelines (ELT) using Databricks, Delta Live Tables, and Databricks Asset Bundles, according to business and technical requirements. • Manage data workflows and orchestration; ensure accuracy and availability of all ELT processes. • Design and deliver silver/gold layer data models within the medallion architecture to support downstream reporting. KRA 2 Platform & Governance • Implemen

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Job Summary As a Data Scientist at Micron, you will employ techniques drawn from mathematics, statistics, and information technology to uncover patterns in data, drive predictive models, and develop actionable solutions for advanced semiconductor manufacturing. Your primary focus will be to support Process Integration and Process Engineering teams to enhance product yield and improve process variation. You will interact closely with multi-functional process areas to solve manufacturing line problems and conduct root cause analysis. In this position, you will help develop software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources—such as inline, param, and probe data—translating them into insights that directly improve process capability and device yield. Key Responsibilities Yield & Process Optimization: Collaborate with semiconductor manufacturing engineering teams to analyze inline/param/probe data to identify top yield detractors and drive continuous improvement. Data Pipeline & Automation: Extract, cleanse, and analyze datasets from SQL databases, sensor networks, and fabrication tool logs to support semiconductor manufacturing operati

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Key Responsibilities Yield & Process Optimization: Collaborate with semiconductor manufacturing engineering teams to analyze inline/param/probe data to identify top yield detractors and drive continuous improvement. Data Pipeline & Automation: Extract, cleanse, and analyze datasets from SQL databases, sensor networks, and fabrication tool logs to support semiconductor manufacturing operations. Advanced Analytics & Modeling: Apply data science techniques, statistical modeling, and machine learning to solve yield issues and support defect reduction strategies. Experimentation Support: Assist process and integration engineers in running and analyzing Design of Experiments (DOE) to enhance process capabilities and margins. Visualization & Communication: Develop automated reports and dashboards using visualization tools (e.g., Dash, Plotly, Angular) to communicate technical concepts and project outcomes effectively to engineering stakeholders. Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. Contributes to a culture of continuous improvement by identifying, testing, and

About the Team OpenAI’s Industrial Compute team is building and productizing infrastructure capabilities that help organizations deploy and operate advanced AI systems at scale. The team works across AI hardware, systems engineering, physical infrastructure, and customer delivery to turn emerging technologies into reliable, repeatable infrastructure solutions. Our work sits at the intersection of technical strategy, product development, engineering, and deployment. We partner closely with customers and internal engineering teams to solve complex infrastructure challenges spanning compute, power, cooling, controls, and facility efficiency. About the Role We are seeking a senior, hands-on Data Center Infrastructure Architect to develop and optimize the physical infrastructure required for large-scale AI deployments. This is a broad technical role spanning data center architecture, electrical and mechanical systems, high-density compute, controls, telemetry, and digital modeling. You will use simulation, operational data, and digital-twin approaches to evaluate infrastructure designs, identify system-level constraints, and improve efficiency, reliability, cost, and speed of deployment. The ideal candidate can move fluidly between first-principles analysis, facility and equipment design, computational modeling, engineering review, and real-world implementation. You should be comfortable working across disciplines rather than operating solely within electrical, mechanical, or software boundaries. Key Responsibilities Define system-level architectures for high-density AI data centers across power, cooling, IT equipment, controls, and facility infrastructure. Develop digital twins and other computational models that represent the behavior of data center systems under changing workloads, environmental conditions, equipment configurations, and failure scenarios. Use design and operational data to identify constraints, improve PUE and related efficiency metrics, and optimize

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Stripe’s GTM Planning and Central Operations team partners with Sales leadership, Finance, Product, Regional Sales Strategy and Operations, and Data Engineering to build the operational processes, tools, policies, and data required to bring our GTM strategy to life. We bring expertise, rigorous thinking, and a user-first approach to problem-solving. We transform, improve, and support Stripe’s global business processes to drive critical initiatives and other cross-functional priorities throughout the sales planning cycle. What you’ll do Build and lead a team of full-time employees and outsourced Sales Operations experts focused on improving our customer data. You will partner with GTM leadership to understand data gaps and address them through processes, policies, and workflows. Responsibilities Apply systems thinking and continuous improvement to the mechanisms owned by the team. Develop a data quality roadmap to address customer data challenges. Align on priorities with leadership, Data Engineering, and Systems teams. Influence the implementation and adoption of systems and tools by working closely with internal systems teams. Create an outsourcing strategy for ongoing data cleanup. Manage contractors as part of the outsourcing strategy to scale data quality initiatives, reporting, processes, and analytics. Define and measure success metrics. Develop dashboards that highlight progress against the identified metrics. Communicate progress

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: As a member of the facilities engineering team, you will design, build, and activate some of the world’s most technically advanced facilities and data centers. As a lead electrical engineer, you will lead a team designing, building, and maintaining power systems that directly contribute to new infrastructure projects. You will be able to operate with autonomy to solve diverse and complex problems, excel at managing multiple projects simultaneously, and work in a dynamic, fast-paced environment. You will work with other MEP engineers, trade partners, and internal customers to support these goals and have the opportunity to drive real global impact, ultimately leading to making life multiplanetary. RESPONSIBILITIES: Lead a team of electrical engineers and work in a team environment with other engineering disciplines to provide detailed electrical design and specifications for the installation of the following equipment and systems: Electrical power distribution systems. Switch-gear and motor control centers. Exterior and interior lighting. Ground support system controls and ladder logic. Uninterruptible power supply (UPS) units. Standby and emergency generato

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Data Scientist II - Decision Science Using data, you will play a crucial role in driving decision-making and delivering impactful insights to our stakeholders. You will apply advanced analytical techniques, build Machine Learning (ML) models, and use experimentation and causal inference methods to solve sophisticated business problems related to platform engagement, product features, and games. What you’ll be doing: Apply advanced statistical and ML techniques to analyse large and complex datasets, extracting actionable insights in a commercial setting. Apply your knowledge of Experimentation, Causal Inference, ML, and statistical modelling to develop robust predictive models and identify causal relationships. Collaborate with cross-functional teams to define business problems, formulate hypotheses, and design experiments to test them. Independently extract and integrate data from multiple data systems, including writing complex SQL queries, to support analytical efforts. Support the delivery of results and presentations to stakeholders, translating complex analyses into clear and actionable recommendations. Stay up to date on the latest advancements in Data Science, including Causal Inference, Gen AI, and ML, and share knowledge and new ideas with the team. What