Data Modelling Consultant Jobs

Leidos is seeking a highly analytical and curious Data Analyst who is passionate about turning data into actionable business insights. The ideal candidate combines strong technical expertise with critical thinking and exceptional communication skills. This role requires someone who can work independently, uncover meaningful patterns in complex datasets, and communicate findings in a way that drives informed business decisions. *The Data Analyst will be a hybrid role, 50% onsite in the Fort Worth, TX office and 50% remote. The candidate for this role must be within commutable distance to the office location. Primary Responsibilities: Extract, clean, transform, and validate data from multiple sources, including relational databases. Write efficient SQL queries to retrieve, manipulate, and analyze large datasets. Develop Python-based data analysis workflows for data exploration, modeling, and reporting. Perform exploratory data analysis (EDA), including univariate, bivariate, and multivariate analysis. Apply statistical methods and predictive modeling techniques such as linear regression and other statistical evaluations. Utilize AI and machine learning tools to identify trends, generate insights, and improve analytical processes. Build and evaluate machine learning models, including: Regression Classification Clustering Decision Trees Supervised Learning Unsupervised Learning Investigate data anomalies and independently determine the root causes behind unexpected results. Identify the most relevant data elements, metrics, and business questions without requiring extensive direction. Translate complex analytical findings into clear, compelling presentations and recommen

About the Role OpenAI’s Industrial Compute organization is responsible for ensuring our compute infrastructure scales efficiently to support millions of users and increasingly sophisticated AI models. We’re looking for a Data Scientist to partner closely with Capacity Systems Engineering, Infrastructure, Product, and Research to optimize inference capacity across our global GPU fleet. This role combines statistical modeling, large-scale data analysis, forecasting, and systems thinking to drive critical decisions around infrastructure investments, performance-efficiency trade-offs, and customer experience. You’ll transform complex operational data into actionable insights that directly influence how OpenAI allocates and scales one of the world’s largest AI compute environments. Key Responsibilities Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency. Develop forecasting models for inference demand across products, regions, and model families. Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities. Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies. Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs. Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions. Collaborate with Product, Research, Finance, and Infrastructure teams to align compute planning with business growth and model roadmaps. Communicate technical findings clearly to both engineering teams and executive leadership. Qualifications MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience). 5+ years of experience working in the infrastructure data science space. Strong ex

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. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem 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 including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

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. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem 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 including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

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. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem 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 including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree in mathematical sciences ( Operations Research, Computer Science, Statistic

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. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem 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 including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree in mathematical sciences ( Operations Research, Computer Science, Statistic

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

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. In this role, the main focus will be on capacity planning, forecasting, and lifecycle management across Micron's global data center and hybrid cloud infrastructure environments. You will partner closely with Manufacturing, Engineering, SMAI, and Corporate IT teams to translate business demand into actionable infrastructure plans while driving capacity optimization, refresh planning, and governance processes. This role will employ AI-enabled tools, advanced analytics, automation, predictive modeling, and digital infrastructure planning capabilities to improve forecasting accuracy, investment decisions, operational efficiency, and infrastructure readiness. You will help ensure compute, storage, network, power, cooling, and facility resources are available to support business growth, operational resilience, AI workloads, and technology modernization across Micron's global infrastructure portfolio! Responsibilities: Capacity Planning & Operations: Maintain a comprehensive view of global infrastructure capacity across on-premises and cloud environments, including compute, storage, network, power, cooling, and rack space. Track available, allocated, landed, and stranded capacity by region, platform, business unit, and service tier. Monitor infrastructure utilization and demand trends to identify capacity risks, utilization opportunities, and gaps against forecasted demand. Partner with infrastructure operations, cloud engineering, SRE, and service owners to ensure capacity supports business and opera

A Career with Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What You’ll Do We are passionate about data. We collaborate to build elegant, effective, scalable, and highly reliable solutions to empower predictive modeling in finance. You will join a team that plays a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe. Specifically, you will: Serve as a frontline owner for thousands of mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with portfolio managers, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s Required Bachelor’s degree with a focus in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments; familiarity with Databricks is a plus. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal

We are seeking a detail-oriented and analytical Data Steward – Operational Technology (OT) to join our Enterprise Data team. The ideal candidate will have a minimum of 3 to 5 years of experience in data management, data quality, and operational technology datasets. In this role, you will be responsible for managing data quality, cataloguing, asset modeling, and data standardization across operational systems (PLC, DCS, SCADA, IoT) and modern cloud data platforms like Databricks. You will work closely with plant operations, IT, data engineering, and analytics teams to ensure high data reliability, consistency, and alignment with enterprise data governance standards. Source: Adani Group | Job ID: 56028

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS. Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph.

About the Role OpenAI's ads platform is experiencing rapid global scale. As the Lead Data Scientist for SMB Ads Growth, you will architect the analytics function end-to-end—driving strategy across targeting, funnel optimization, and performance forecasting. You will work directly with the SMB Ads Marketing team and your insights will be the primary catalyst for high-stakes decisions across marketing, product, and sales engineering. What You'll Do Full-Funnel Analytics Establish the foundational growth metrics and North Star KPIs for the SMB Ads ecosystem, optimizing the journey from lead acquisition to long-term retention. Diagnose funnel friction points through advanced behavioral analysis and quantify the incremental revenue impact of proposed optimizations. Partner cross-functionally to transform complex data findings into actionable, high-priority roadmaps for product and marketing stakeholders. Targeting, Segmentation & Propensity Modeling Engineer sophisticated propensity models and look-alike frameworks to identify and capture high-LTV SMB advertisers. Own the lifecycle of target list construction, including advanced data enrichment, multi-dimensional prioritization, and granular performance tracking. Develop robust segmentation architectures that power hyper-personalized outreach across paid, partnership, and outsourced (BPO) channels. Synthesize market signals to refine our value proposition, ensuring OpenAI remains a key platform for SMB business growth. Campaign Analytics & Measurement Design and implement rigorous multi-touch attribution and incrementality frameworks to evaluate channel efficacy. Lead the experimental roadmap: formulate hypotheses, execute A/B and multivariate tests, and communicate results to executive leadership. Automate business-critical reporting and dashboards to provide real-time visibility during weekly operating reviews. Forecasting & Planning Build high-fidelity revenue and advertiser growth models to project perfor

Sr. Data Scientist The team + the role Pendo's GTM Intelligence Team turns data into measurable outcomes across Sales, Marketing, and Customer Engineering. We combine analysis, ML models, and internal tooling to answer high-value business questions and help GTM teams work faster and more effectively. We measure success by the real business value our work creates. As a Senior Data Scientist, you'll own the full lifecycle of intelligence solutions, from problem definition and analysis through model development, stakeholder enablement, and ongoing iteration. You'll work directly with GTM teams to surface high-value business problems and answer them with the right mix of analytics and modeling, translating what you find into decisions that stick. The best person for this role has strong modeling instincts, genuine curiosity about how GTM businesses operate, and the judgment to know when a complex model is the right tool — and when a well-framed SQL query gets you there faster. This role is based in Raleigh, NC and follows Pendo's hybrid model: in-office 3 days per week. What this looks like day-to-day Leverage data analysis, machine learning, and predictive modeling to identify opportunities and mitigate risks for our GTM teams, from problem framing through delivery and ongoing iteration Work collaboratively with data & AI engineers, analysts, revenue operations, and GTM stakeholders to ensure your work is actionable, interpretable, and clearly connected to business decisions Translate model outputs and analytical findings into clear business narratives through slides, write-ups, presentations, and async video Leverage AI-assisted development tools (Cursor, Claude Code) to accelerate delivery and prototype faster, while applying the critical thinking to validate, refine, and own the output Share and build reusable patterns, model documentation, and technical findings with the broader team Answer high-value business questions through analysis and experimentation: dev

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS. Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph.

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 . What you’ll do: Be the technical lead for the forecasting team . Own the strategy and implementation of forecasting models of key company metrics (e.g., monthly active users), delivering accurate, interpretable forecasts at scale. Lead the full modeling lifecycle end to end : problem framing, feature engineering, model development and prototyping, experimentation and backtesting, deployment, monitoring/drift detection, and explainability. Set the forecasting technical vision. Define model architectures and standards, and partner with Engineering to shape the forecasting platform for efficient training/inference today and the scalability needed for the next generation of models. Translate forecasts into decisions. Present outputs, scenario analyses, and recommendation frameworks to senior leadership with clarity and brevity. This is a high‑visibi