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Data Analyst Jobs

8,120 active opportunities · Updated for October 2026

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Explore current data analyst jobs. Use filters to narrow by work mode, employment type, experience and date posted.

O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

awsrestmachine learning
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O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team Codex is OpenAI’s first-party developer product focused on agentic software engineering. We’re building tools that help engineers design, write, test, and ship code faster—safely and at scale. We partner tightly with research and product to translate model advances into tangible developer productivity. About the Role As a Data Scientist on Codex, you will measure and accelerate product-market fit for AI developer tools. You’ll define what “developer productivity” means for our product, run experiments on new coding models and UX, and pinpoint where the model helps or hurts across languages and tasks. Your insights will directly shape how an entire industry builds software. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Embed with the Codex product team to discover opportunities that improve developer outcomes and growth Design and interpret A/B tests and staged rollouts of new coding models and product features Define and operationalize metrics such as suggestion acceptance, edit distance, compile/test pass rates, task completion, latency, and session productivity Build dashboards and analyses that help the team self-serve answers to product questions (by language, framework, repo size, task type) Diagnose failure modes and partner with Research on targeted improvements (model quality signals, user feedback, evals) You might thrive in this role if you have 5+ years in a quantitative role at a developer-facing or high-growth product Fluency in SQL and Python; comfort with experiment design and causal inference Experience defining product metrics tied to user value Ability to communicate clearly with PM, Eng, and Design—and to influence product direction You could be an especially great fit if you have Strong programming background; ability to prototype, run simulations, and reason about code quality Familiarity with IDE/extensi

pythonsqlaws
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O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team Our infrastructure team helps deliver OpenAI’s most capable models and products to the world by scaling infrastructure and turning demand into useful FLOPS. We collaborate across research, engineering, design, and business to turn cutting-edge AI advancements into impactful, real-world applications. Our team ensures the right compute is available—at the right time and place—to support some of the world’s most demanding workloads. We empower all of OpenAI’s products and research by scaling the infrastructure behind them. Our work makes it possible to launch new models and products reliably and at scale. About the Role As a Data Scientist on the Infra team, you will play a key role in shaping how we scale the infrastructure that powers OpenAI’s products and research. This is critical as we operate one of the largest and most advanced compute fleets in the world, supporting millions of users and businesses globally. We focus on aligning infrastructure measurement, planning, scaling, allocation, and efficiency to drive measurable impact across the company. You should expect to guide the definition of foundational datasets for infrastructure resources, develop metrics that inform key decisions, build forecasting and optimization models, and establish source of truth dashboards and analyses that enable teams to understand and improve infra usage. Most importantly, you should expect to be a core partner to engineering, research, and product teams in shaping the infrastructure that powers everything OpenAI builds. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Build and maintain foundational datasets and metrics that reflect infrastructure usage, efficiency, and scaling. Develop forecasting and optimization models to support infra planning and resource allocation. Partner with engineering, research, and product teams to shape infrast

pythonsqlaws
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O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework . Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models. The mission of the Preparedness team is to: Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards misuse risks whose impact could be catastrophic to our society Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems Preparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society. About the Role We’re hiring a Data Scientist to help build, evaluate, and continuously improve mitigations that prevent extreme harms from AI systems. This role is for an experienced, highly autonomous individual contributor who can take ambiguous problem statements, structure rigorous analyses, and translate findings into actionable product and policy changes. This position goes beyond “running evals.” You’ll help create mitigation intelligence and monitoring systems that enable OpenAI to detect issues early, measure effectiveness over time, and reduce both over-blocking (unnecessary friction) and under-blocking (missed harm). What You’ll Do Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains (e.g., biosecurity, cybersecurity, and emerging risk areas). Diagnose false positives and fa

pythonsqlaws
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Notion
📍 San Francisco• Full-time• $210K – $260K/yr
1mo ago

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: You'll be Recruiting's dedicated people analytics partner — owning the data, shaping the strategy, and in the room where decisions get made. The core of the role is building trusted recruiting analytics infrastructure (funnel + stage conversion, pipeline aging, time-to-fill, offer acceptance, sourcing channel quality, and recruiter capacity) and making it self-serve for recruiters and leaders. You’ll own the stack end-to-end — from raw data in Ashby and Snowflake to clear insights that hold up in a pipeline review. You're the person who turns workforce signals into recruiting strategy — bringing a point of view. This role may be based in either our San Francisco or New York City offices. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Own recruiting analytics end-to-end: Build and maintain the dashboards and reporting infrastructure Recruiting leadership relies on (funnel health, conversion rates by stage, time-to-fill,

sqlrestai
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Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: You're joining Notion's People Analytics & Operations team as part of an 18-month rotational program -- the group that builds the insights engine powering every people decision Notion makes. We look for slope over intercept. We care less about where you trained and more about what you've built. If you've ever rebuilt a broken process because it was bothering you, used AI to do something you couldn't have done alone, or found yourself reading about labor economics for fun -- you're the person we're looking for. Over 18 months, you'll rotate across people operations, people analytics, and compensation/benefits. Every rotation is real work with real ownership. On the analytics side, you'll build dashboards that land in exec review, write SQL that powers headcount models, and prototype AI-assisted workflows that help our team move faster. On the operations side, you'll run the HR engine -- managing employee lifecycle transactions in Workday, owning onboarding and offboarding coordination end-to-end, triaging and resolving employee requests, and keeping our people data clean and audit-ready. You'll be paired with a sen

pythonsqlrest
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PE
Private Employer
📍 Uttar Pradesh, India• Full-time
1mo ago

Manager - HR Analytics (MIS) About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. Role Overview We are seeking an experienced and detail-oriented professional to lead our HR MIS function while also managing strategic HR programs and projects. The role combines strong analytical and reporting expertise with program management capabilities, ensuring HR initiatives are data-driven, efficiently executed, and aligned with organizational goals. Key Responsibilities 1. MIS (Management Information System) & Analytics ● Lead design, automation, and governance of HR dashboards, reports, and analytics. ● Ensure timely and accurate reporting of workforce metrics (headcount, attrition, hiring, productivity, compensation, compliance, etc.). ● Partner with HR and business leaders to translate data into actionable insights. ● Provide support in driving end-to-end planning, execution, and monitoring of HR strategic programs (engagement, digitization, capability building, data compliance, etc.). ● Build predictive models for workforce planning, attrition, and productivity. ● Act as the central point of contact for managing all associated leadership presentation. ● Provide data-backed recommendations for policy, process, and people decisions. ● Build capability within HR teams for better use of data and program management. 2. Program Management (HR Transformation Strategic Projects) ● Support Head Transformation in managing program objectives, milestones, success metrics, and governance structures; escalate proactively. ● Collaborate with cross-functional teams, vendors, and HR CoEs to ensure program success. Qualifications & Experience ● Postgraduate degree (MBA/PGDM – HR, Business Anal

sqlgitai
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PE
1mo ago

About the Role We are looking for a seasoned Engineering Manager to lead our Data Platform. You will own the architecture and evolution of a Petabyte-scale Data Lakehouse and a Self-serve Analytics Platform, enabling real-time decision-making across the organization. In this role, you will drive consistency and quality by defining the right engineering strategies. You will oversee multiple engineering projects, ensure timely execution, collaborate across functions, and mentor engineers to grow into high-performing contributors.

TaylorMade Golf is a global leader in golf equipment, driven by relentless innovation across clubs, balls, and accessories. Our North America Operations team balances service, demand, and supply across a fast-moving, seasonal portfolio. The Senior Manager, Supply Chain Analytics & S&OP is the analytical backbone of TaylorMade's North America Operations team. This role sits at the intersection of Sales, Supply Chain, Finance, and Operations — translating complex data into clear, actionable insights that drive cross-functional alignment and continuous improvement across the S&OP cycle. This individual provides leadership visibility into key performance trends through reporting, data validation, and analysis across planning, service, inventory, logistics, and operations. They also lead and develop a team responsible for delivering accurate analytics and strengthening business intelligence capability across the North America Operations organization. Essential Functions and Key Responsibilities: S&OP Analytics & Process: Supports the North America S&OP process by preparing analytics and review materials that align Demand Management, Supply Planning, Sales, Finance, and Operations around demand, supply, service, and inventory considerations. Directs the team's preparation of pre-read materials, variance narratives, and executive-level presentations for monthly S&OP cycles, lessons-learned reviews, and consensus forecast sessions. Develops scenario and trade-off analysis for executive reviews to support decisions on capacity allocation, product priorities, service levels, and inventory balance. Partners with Sales, Demand Management, and Supply Planning to identify root causes of forecast bias, service performance gaps, and planning misalignment. Contributes to S&OP process maturity initiatives — documentation, playbook development, gover

SAPExcelPower BI
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P
15 days ago

What You Will Achieve As a Senior Scientist, you will be at the center of our operations and you’ll find that everything we do, every day, is in line with an unwavering commitment to quality. You will be recognized as a technical expert and a scientific contributor. With your deep knowledge of the discipline, you will be an active team member whose decisions impact the projects. You will perform qualitative and quantitative analyses of organic and inorganic compounds to determine chemical and physical properties during chemical syntheses, or drug product development process. You will be using your scientific judgment to adapt standard methods and techniques by applying prior work experience. You will be forecasting and planning resource requirements for your project team. Your creativity in developing novel processes and new ideas will be used frequently. You will undertake mentoring activities to guide team members. It is your innovative scientific temperament that will help in making Pfizer ready to achieve new milestones and help patients across the globe. How You Will Achieve It This colleague will be responsible for developing analytical strategies in support of pharmaceutical drug substance and/or drug products during all development phases, including supporting manufacturing process development, developing, validating and transferring analytical methods, designing stability studies for shelf life assignments, and developing impurity control strategies. Collaborates with colleagues and subject matter experts to assess the most appropriate analytical approach to support project activities, including use of computational predictive tools, modelling software and data visualization tools where appropriate. Perform lab work and delegate responsibilities and review peer lab work as appropriate, Through effective communicat

airecruitment
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C
Cvshealth
📍 Work From Home, United States• Remote
16 days ago

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. POSITION SUMMARY CVS Health is seeking a highly skilled Staff Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Staff Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Staff Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices. Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Staff Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patterns. The id

REMOTEpythonsqlazure
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I
Illumina
📍 California• $141.6K – $212.4K/yr
16 days ago

What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible. Summary The Staff Data Engineer is a seasoned, hands-on engineer who designs, builds, and scales data products on our cloud lakehouse, powering analytics, reporting, and AI/ML across Illumina. We are looking for someone with strong proficiency in Python, SQL, and data modeling, a solid understanding of distributed systems and system design who has built and scaled data products on modern cloud platforms such as Databricks and Snowflake. This is a hands-on, senior individual-contributor role with end-to-end ownership and leadership spanning multiple domains such as Supply Chain, Manufacturing and Quality, including mentoring engineers on our global (India-based) team. Responsibilities Partner across business, AI, and platform teams translating domain needs (e.g., SAP, Manufacturing, Quality) into well-modeled, governed and scalable data products. Design, build, and scale end-to-end data products on Databricks (and interoperating with Snowflake) — from ingestion through curated, analytics-ready datasets following a medallion (Bronze/Silver/Gold) architecture. Develop reusable frameworks, libraries, and

pythonsqlaws
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C
18 days ago

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. POSITION SUMMARY CVS Health is seeking a highly skilled Senior Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Senior Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Senior Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices. Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Senior Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patter

REMOTEpythonsqlazure
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F
18 days ago

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma’s Data Science team partners across product, engineering, design, marketing, sales, and operations to help Figma make better decisions with data. As a PhD Data Science Intern, you’ll bring rigorous research training to some of Figma’s most important and open-ended questions, from researching emerging product and user behaviors and Figma’s broader ecosystem to developing new measurement methodologies, applying causal inference or machine learning, and building analytical systems. You’ll own a data science project end-to-end: from framing the question and methodology to translating findings into insights that influence Figma’s products, strategy, or data science practices; with the potential to continue toward publication after the internship. This internship will be based out of our San Francisco or New York hub. What you’ll do at Figma: Partner with cross-functional teams to turn ambiguous product, platform, or business questions into well-defined data science problems Analyze user, product, or business data to uncover insights and recommend actions Design and evaluate experiments, metrics, statistical or machine learning models, and analytical frameworks Communicate assumptions, tradeoffs, limitations, and recommendations clearly to technical and non-technical partners Own a focused internship project end-to-end, from problem framing and technical execution through final recommendations, with potential to continue toward publication after the internship We’d love to hear from you if you h

pythonsqlmachine learning
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E
EVERY™
📍 San Francisco• Full-time• $900K – $1M/yr
22 days ago

About us EVERY™ is a leading VC-backed food tech ingredient company and market leader using precision fermentation to create animal proteins without the animal for the global food and beverage industry. EVERY™ is a team of passionate change-makers who are reimagining the factory farm model with a kinder, more sustainable alternative. Leveraging precision fermentation to produce hyper-functional and one-to-one replacement proteins from microorganisms, EVERY™ is on a mission to decouple the world’s proteins from the animals that make them. We are a passionate, determined (and fun!) team with a vital objective, and we're on the lookout for like-minded people to join our mission. For more information, visit www.every.com The Role: This unique entry-level Research Associate I position offers the rare chance to work across two core teams, Analytics and Protein Science. You’ll gain hands-on experience supporting protein development, purification, and analysis, while learning how these disciplines work together to drive innovation in precision fermentation. This is a great opportunity for someone early in their career who thrives in the lab, loves variety, and wants to learn fast in a collaborative, mission-driven environment. What you'll accomplish Generate data through basic biochemistry/molecular biology techniques (including but not limited to BCA, SDS-PAGE) Operate and maintain analytical equipment (e.g., HPLC-UV/RI and Combustion Analyzer, dynamic light scatterer, FPLC-UV, fluorescence/UV plate reader) Support protein characterization workflows through lab-scale protein powder generation involving bench-scale downstream processing unit operations (microfiltration, ultrafiltration, diafiltration) Prepare samples, reagents, and buffers to support cross-functional experiments Collaborate with scientists and engineers across teams to troubleshoot and iterate quickly as part of our Design, Build, Test, and Learn pipeline Present results

aigolean
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