Data Modelling Consultant Jobs

We are seeking a highly skilled and experienced Data Scientist to join our Perception Verification and Validation team. The team is responsible for verifying and validating the perception stack of our autonomous driving system. The candidate will work closely with other data scientists, perception engineers, and systems engineers to develop datasets and metrics to quantify the performance of our perception system. The candidate will also help define key performance metrics that will enable perception engineers to directly measure the impact of new features on both the overall Perception stack as well as end-to-end system behavior. In this role, You will... Define key performance metrics that will help perception engineers to measure the impact of new features on the perception stack and the end-to-end system behavior Create and maintain datasets used to evaluate the perception stack and end-to-end driving performance. Analyze large scale metric results to identify patterns and insights about perception failure modes. Present results and insights to leadership. Design and implement statistical methods to quantify uncertainty in our performance and validation metrics. Qualifications Master's or PhD degree in Statistics, Mathematics, Computer Science, or a related field Proficient using data query languages (SQL and/or Spark/scala) to quickly build complex yet efficient data queries at scale and using Python to build production-quality code Basic experience with autonomous driving, safety-critical systems, or computer vision systems. Proficient in exploratory data analysis (EDA) and data visualization to understand and present trends and their implications for the business. Background in statistical modeling and analysis; including experience making data-driven decisions that connect point and uncertainty estimates to business impact. Bonus Qualificati

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsibilities include, but not limited to: Strong desire to grow a career as a Data Scientist in highly automated industrial manufacturing doing analysis and machine learning on terabytes and petabytes of diverse datasets. Experience in the areas: statistical modeling, feature extraction and analysis, supervised/unsupervised/semi-supervised learning. Exposure to the semiconductor industry is a plus but not a requirement. Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques. Strong software development skills. Strong verbal and written communication skills. Experience with or desire to learn: Machine learning and other advanced analytical methods Fluency in Python and SQL GCP and/or another SQL databases Experience with or desire to learn Google Cloud Vertex AI, AI/ML pipeline development, LLM applications, AI agents, Model Context Protocol (MCP), and skill/tool orchestration frameworks for enterprise AI solutions. Experience working with time-series data, images, semi-supervis

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

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. WHY DATA SCIENCE & ANALYTICS? The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product groups, we use this vast tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure the impact on our community of players and developers. WHY Consumer Apps? Roblox is used by tens of millions of people every day across a wide range of devices, including mobile, desktop, console, TV, and VR. The Consumer Apps team owns the app foundation that makes Roblox feel fast, fluid, and reliable for players and is dedicated to delivering superior performance, reliability, and user experience across all platforms Roblox supports. This team ensures a seamless and engaging user interface that facilitates intuitive interactions while enabling efficient, high-quality experiences

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Data Science sits at the heart of how Coinbase builds products and makes decisions. We partner with Product, Engineering, and Design to shape roadmaps, understand our users, and move the company's bottom line through rigorous experimentation, analytics, and advanced modeling. As a Data Scientist on the Consumer team, you'll improve the customer experience across Coinbase's consumer products — including spot and advanced trading, yield, Coinbase One, international expansion, and new launches such as prediction markets and equities trading. You'll define key metrics, build measurement and causal frameworks, and translate insights directly into product strategy and shipped improvements. What you'll do: Drive analysis and deep dives on ambiguous business problems, delivering insights and recommendations that guide team decision-making Own a broad scope of data and metrics — from core logging to polished data visualizations Lead code reviews, contribute SQL and Python expertise, and maintain reliable ETL pipelines Uphold a high bar for statistical rigor, ensuring experimentation and causal analyses build genuine confidence with stakeholders Required Skills and Experience: BA/BS in a quantitative field (Math, Stats, Physics, CS, or similar) with 5+ years of relevant experience, or a PhD with 3+ years of relevant experience Proven track record of delivering impa

About the team The Monetization Data Platform team builds the trusted data and platform foundations that power how the company develops, measures, and improves monetization products. We bring together product usage, pricing, billing, ads, payments, and financial data to help Product, Engineering, Finance, and GTM teams make better decisions and deliver reliable customer experiences. We work at the intersection of data engineering, product engineering, platform engineering, Finance, and GTM. Our goal is to turn complex monetization and financial data into accurate, explainable, and timely data products while building systems that scale with the growth and complexity of the business. About the role We are looking for a Data Engineer to improve and build the next generation of our monetization data platform. You will own high-impact systems end to end, from product instrumentation, source ingestion, and canonical modeling through quality controls, observability, and delivery to downstream consumers. This is a hands-on role for an engineer who enjoys solving ambiguous product and data problems, designing durable architectures, and partnering closely with Product Engineering, Finance, Accounting, and GTM. You will help define technical direction, raise the engineering bar, and turn monetization opportunities into trusted, scalable data products and platform capabilities. In this role, you will Design, build, and operate large streaming and batch data pipelines that process product, financial, and operational data from a variety of internal and external systems. Develop canonical data models and reusable data products for domains such as product usage, pricing, billing, ads, payments, revenue, and the general ledger. Establish strong guarantees for data accuracy, completeness, freshness, lineage, reconciliation, and auditability. Build frameworks and platform capabilities that improve developer productivity and make it easier for teams to launch, measure, and iterate on m

Who We Are Artefact is an applied AI company. We build systems that run in production, in our clients' own cloud, and keep running after we leave. 2,500+ people across 27 countries and 1,000 clients, including some of the largest consumer brands in the world. Not a strategy house that discovered AI eighteen months ago, and not a prototype shop that hands you something you will rebuild from scratch. Three ingredients make that possible, and very few firms have all three: the data, real and messy and at enterprise scale; an applied AI team that can put a model into a governed production environment; and the transformation muscle to make people actually use it. Agentic AI lands on marketing before it lands anywhere else. Agents browse, compare and buy; clicks stop meaning what they meant; the shelf turns into an API. Every senior marketing and commerce leader we talk to is asking the same two questions — am I still visible, and can I still prove what worked — and almost nobody can answer them. The Role We are hiring a Director to lead marketing measurement and effectiveness for our US client portfolio, starting with a large, in-flight measurement program for a major US financial services client. This is a player-coach role. You will own the methodology and the client relationship, lead a multi-workstream data science team, and stay close enough to the models to challenge assumptions, review code and unblock hard technical problems yourself. You will also help us productize what we build — turning measurement work into reusable accelerators and points of view that scale across accounts. You should be able to step into a live, complex measurement program quickly and earn credibility with senior client stakeholders in the first weeks, not the first quarter. What You'll Do You will own the hardest question in marketing: what actually caused the sales. Marketing Mix Modeling, incrementality testing, geo-lift, attribution — for a brand where a few points of budget reallocati

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. WHY DATA SCIENCE & ANALYTICS? The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers. WHY DISCOVERY EXPERIENCES? Roblox is not just a platform; it is a complex, two-sided marketplace where millions of creators meet over 70 million daily active users. The Discovery Experiences team is the technical heartbeat of this ecosystem. We own the surfaces—Home, Search, Matchmaking, and Notifications—that determine how users navigate the metaverse. As a Data Scientist , you will own the ranking initiatives that power these canvases. You aren't just building models; you are building the economic and social f

Fanatics Commerce is the global leader in licensed sports merchandise, operating a vertically integrated platform that designs, manufactures, and delivers officially licensed apparel, jerseys, headwear, and collectibles for major leagues, teams, and events worldwide. With more than 900 e-commerce sites and a global omnichannel presence across digital, in-venue, and retail, Fanatics Commerce reaches fans in over 180 countries and powers official fan experiences for many of the world's most iconic sports properties. At Fanatics, we bring our BOLD Leadership Principles to life every day - building championship teams, obsessing over fans, acting with entrepreneurial speed, and delivering with a determined and relentless mindset. As we continue to scale our global platform, the Senior Data Scientist, Supply Chain & Inventory Optimization will play a critical role in maximizing supply chain efficiency and inventory financial performance through ML-driven modeling, pricing optimization, and demand forecasting. ROLE OVERVIEW This role sits within a high-impact team responsible for product lifecycle modeling, pricing and promotional optimization, clearance management, demand forecasting, network simulation, and inventory sourcing, allocation, and balancing. The Senior Data Scientist will bring a rigorous, ML-driven mindset across operational modeling, forecasting, pricing, and product strategy — moving fluidly across domains in a collaborative, fast-moving team culture with a strong emphasis on delivering measurable business impact amid frequently shifting requirements. The Senior Data Scientist delivers business and fan impact through BOLD leadership and execution excellence, leveraging data, automation, and AI-enabled insights. HOW WILL YOU DRIVE IMPACT Success is measured by the ability to deliver results through BOLD capabilities and measurable outcomes. Team & Leadership Impact (Build Championship Teams) Partner cross-functionally with engineering, product, and

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Data Engineer, you’ll be responsible for laying the foundation for a best-in-class analytics function. You’ll partner closely with our engineering team and business stakeholders to ensure that our analytics stack and processes meet the business needs today with an eye towards the future. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as a Senior Data Engineer at Vanta: Design and deploy data infrastructure needed to drive data-driven decision-making solutions Design and implement complex data orchestration models, modeling metadata, scaling reporting tools for data science and ML products users Be the company’s expert on data administration, data management and scalable data systems Write highly tuned, scalable SQL queries running over large-scale, heterogeneous data warehouses Work with the Product and Enterprise Engineering system teams to structure source systems for reporting consumption across the enterprise Help maintain CDC pipelines to power customer reporting Help develop front end applications to expose analytical data sets enterprise wide How to be successful in this role: Have at least four years of experience working with data and two years of experience in Software Engineering or a related field. Have experience with common analytics tooling (e.g. Stitch/Fivetran, Snowflake/BigQuery/Redshift, dbt, Airflow, Dagster). Have good working knowledge of AWS data infra systems and Terraform. Bring a system-oriented and software engineering mindset to the Data Engineering practice. We’re looking to build frameworks that manage data, and minimize bespoke queries Deep kn

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. WHY DATA SCIENCE & ANALYTICS? The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers. WHY AUTHENTICATION & SECURITY? Authentication & Security sits at the intersection of trust, product, and growth. The team builds the systems that allow users to sign in, recover, and protect their accounts with confidence, while defending the platform against account takeovers, credential abuse, and fraud at massive scale. This role is an opportunity to shape a high-stakes product area where small changes in friction or protection can meaningfully affect sign-ups and user frequency. You will act as a strategic leade

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 Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our Fraud, Losses, and Financial Crime Data Science team builds the models and data products that protect Stripe and its users from fraud, account takeover, and financial crime. We own the full fraud and loss modeling stack - from account takeover detection and card fraud classification to merchant-level loss estimation, unsupervised anomaly detection, and financial crime risk modeling. We partner with Fraud Engineering, Financial Crimes Engineering, and Risk Operations to bring these systems into production and ensure they have measurable impact on Stripe's financial integrity and user trust. What you'll do We're looking for a Data Scientist to join the Fraud Data Science team. In this role, you'll build and improve the models that power Stripe's fraud detection and loss management systems. You'll work closely with Fraud Engineering and Risk Operations to move models from research to production, and you'll use data to surface insights that shape fraud strategy across the business. Data scientists on this team apply supervised and unsupervised machine learning, statistical mod

About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About the Role We're looking for a Senior Data Analyst, Marketing to join our Data Intelligence team and build the measurement foundation that tells us what's actually working across paid and PLG channels. You'll work closely with Marketing, Growth, and channel owners, helping us move past platform-reported metrics and vanity numbers into causal, trusted answers about what drives pipeline and revenue. This role is ideal for someone who thrives in async, fast-paced environments, is AI-forward in how they work, and is excited about building a measurement function from the ground up. What You'll Be Responsible for Marketing Measurement Strategy Own the end-to-end marketing measurement strategy across experimentation, media mix modeling, and attribution for paid and PLG channels Establish and evolve the attribution framework: how platform data, multi-touch attribution, MMM, and experiments work together to inform decisions Translate complex measurement outputs into clear recommendations on where to invest, what to cut, and how to hit pipeline, revenue, and efficiency targets (CAC, payback, LTV to CAC) Serve as the subject matter expert for marketing measurement, educating stakeholders on causality, model uncertainty, and the limitations of platform-reported metrics Incrementality and Experimentation Design and run always-on incrementality tests, user-level and geo-level, to quantify the causal impact of key channels, campaigns, and tactics Calculate incremental lift, incrementality percent, and incremental ROAS/CPA, and use these to guide budget reallocation Build repeatable analysis templates and playbooks for experiment design, analysis, and readouts so results are consistent across teams Partner

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsibilities include, but not limited to: Strong desire to grow a career as a Data Scientist in highly automated industrial manufacturing doing analysis and machine learning on terabytes and petabytes of diverse datasets. Experience in the areas: Agentic AI, statistical modeling, feature extraction and analysis, supervised/unsupervised/semi-supervised learning. Exposure to the semiconductor industry is a plus but not a requirement. Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques. Strong software development skills. Strong verbal and written communication skills. Experience with or desire to learn: Machine learning and other advanced analytical methods Fluency in Python and/or R pySpark and/or SparkR and/or SparklyR Hadoop (Hive, Spark, HBase) Teradata and/or another SQL databases Tensorflow, and/or other statistical software including scripting capability for automating analyses SSIS, ETL Javascript, AngularJS 2.0, Tableau Experience working with time-series data, images, semi-supervised learning, and data with frequently changing distributions is a plus Experience working with Manufacturing Execution Systems (MES) is a plus Existing papers from CVPR, NIPS, ICML, KDD, and other key conferences are plus, but this is not a research position About

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Staff Data Scientist on the Data Science team within the Platform group, you'll own pricing experimentation and strategy for Coinbase's Consumer & Business products. This team partners directly with Product, Engineering, and Design to turn deep analytical expertise into decisions that move the company's bottom line. You'll design and analyze pricing tests, build models that identify optimal strategies, and communicate findings to executives and cross-functional leaders. What you'll do: Own end-to-end pricing experimentation, from test design through analysis and recommendation Build and refine pricing models and evaluation frameworks that determine optimal pricing strategy across consumer products Partner with Product, Engineering, and Finance stakeholders to develop pricing vision, roadmap, and priorities Develop and maintain data pipelines and data models that power pricing analytics with production-grade craftsmanship Synthesize complex findings into clear, actionable recommendations and present them to senior leadership Required Skills and Experience: 8+ years of experience in data science with a focus on pricing experimentation, causal inference, and statistical modeling (PhD preferred, or Master's in Economics, Statistics, or related quantitative field) 5+ years directly leading pricing or experimentation workstreams, including designing A/B tests and