Data Modelling Consultant Jobs

US Consumer Sales - Amazon Project Manager Description - This Project Manager role will work directly with Amazon and this person will be part of the US Consumer Sales organization. This person will specifically focus on the operational side of our business with Amazon and be responsible for all operational chargebacks. If HP does not meet the operational expectations of Amazon, then Amazon can send a chargeback penalty to HP. This project manager will track all penalties and work very closely with internal and external partners to identify and correct the root cause to avoid further penalties. This project manager is responsible for saving a very significant amount of money for HP. The role monitors performance metrics, identifies opportunities for improvement, and ensures alignment with strategic objectives and regulatory compliance. Responsibilities • Work directly with the sales team as well as every category (Print, Supplies, PS, and Peripherals). • Engage with various teams within Amazon to also identify root-causes and corrective actions. • Supports the execution of strategic plans for the improvement and optimization of business processes and capabilities across the organization. • Designs the architecture of key processes and capabilities, ensuring that they are aligned with the overall business architecture and long-term vision. • Collaborates with various departments and business units to ensure that processes and capabilities are integrated seamlessly into the broader organization. • Utilizes data analytics and modeling techniques to identify trends, patterns, and opportunities for process improvement, cost reduction, and revenue enhancement. • Monitors performance metrics and KPIs for processes and capabilities and provides insights for improvement. • Utilizes standard project management and quality improvement methodolog

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for a Data Engineer II to help us build the next generation of products which will go beyond just ID and enable our members to leverage the power of a networked digital identity. As a Data Engineer at CLEAR, you will participate in the design, implementation, testing, and deployment of applications to build and enhance our platform- one that interconnects dozens of attributes and qualifications while keeping member privacy and security at the core. A brief highlight of our tech stack: SQL / Python / Looker / Snowflake / dbt What you'll do: Build a scalable data system in which Analysts and Engineers can self-service changes in an automated, tested, secure, and high-quality manner Build processes supporting data transformation, data structures, metadata, dependency and workload management Develop and maintain data pipelines to collect, clean, and transform data (owning end to end data product from ingestion to visualization) Develop and implement data analytics models Partner with product and other stakeholders to uncover requirements, to innovate, and to solve complex problems Have a strong sense of ownership, responsible for architectural decision-making and striving for continuous improvement in technology and processes at CLEAR What you're great at: 4+ years of data engineering experience Working with cloud-based application development, and be fluent in at least a few of: Cloud services providers like AWS Data pipeline orchestration tools like Airflow, Dagster, Luigi, etc Big data tools like Spark, Ka

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview As a Member of Technical Staff in Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data. You will work closely with researchers and annotation teams so they can iterate on data as quickly as they iterate on models. Key Responsibilities Build and maintain data pipelines for SFT, preference, and RL post-training data. Own dataset quality, versioning, and reproducibility. Turn research data recipes into production-grade, reusable components. Scale model inference for data generation and model-based grading. Design data formats and schemas that keep post-training datasets consistent and efficient to train on. Collaborate with researchers and engineers to make sure data pipelines keep pace with the needs of cutting-edge language models. Qualifications Strong software engineering skills. Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training. Track record of running distributed data processing and model inference at

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Member of Technical Staff in Data Analysis and Evaluation, you will play a pivotal role in ensuring the quality, reliability, and performance of our large language models (LLMs). Your primary focus will be on designing and conducting data collection tasks, assessing and evaluating dataset quality, and analysing the robustness and generalisability of our models. You will work closely with cross-functional teams, including researchers, engineers, and data annotators, to conduct data-driven decision-making and improve the overall effectiveness of our AI systems. This role combines expertise in statistics, experimental design incl. human annotators, and machine learning to ensure that our models are trained on high-quality data and perform reliably across diverse scenarios. You will contribute to Cohere’s mission of advancing AI by ensuring our systems are robust, scalable, and impactful. Please Note: We have offices in London, Paris, Toronto, San Francisco, and New York, but we also embrace being remote-friendly! There are no restrictions on where you can be located for this role. Key Responsibilities: Design an

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Senior Member of Technical Staff specializing in web data for pre-training, you will play a pivotal role in developing the large scale web data pipeline that underpins Cohere’s advanced language models. In this role, you will work extensively with large-scale web corpora, transforming raw, noisy internet data into high-quality training data for pretraining. You will own key components of the data pipeline, including extraction, parsing, deduplication, and filtering. You will also analyze the composition and quality of web data, study its impact on downstream model performance, and collaborate closely with the broader data and evaluation teams to iterate on the training corpus. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace bein

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Senior Machine Learning Engineer specializing in synthetic data, you will play a pivotal role in developing the synthetic data pipeline that is crucial to Cohere’s advanced language models. Your responsibilities will encompass the end-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, as well as conducting data ablations and model evaluation to gauge data quality. You will work with diverse web data and code data and transform them using generative models to improve token efficiency and model quality. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Machine Learning Engineer specializing in pretraining data, you will play a pivotal role in developing the data pipeline that underpins Cohere’s advanced language models. In this role, you will conduct data ablations to evaluate data quality and construct pre-training data mixtures to enhance model performance. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role between EST and EU. Key Responsibilities: Conduct data ablations t

Data Analyst V itD is seeking a Data Analyst V to analyze customer experience and customer support data for Reality Labs, uncover actionable insights, and improve customer satisfaction across the end-to-end customer journey. The ideal candidate will bring 8+ years of experience in data analytics or data science, strong SQL and Python or R programming skills, and expertise in statistical modeling, predictive analytics, and Generative AI to translate complex customer data into insights that drive business improvements and customer-centric decisions. Location : Remote – US (Candidates must be able to work Central or Pacific Time hours) Duration : 12 months, with potential for extension or conversion Schedule : 40 hours per week, Monday–Friday; no overtime. We provide comprehensive medical benefits, a 401k plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship. Responsibilities Analyze large, complex datasets using SQL, Python or R, and statistical techniques to identify customer experience trends, pain points, and opportunities for improvement. Synthesize customer signals from surveys, digital analytics, behavioral data, operational metrics, and customer support interactions across the end-to-end customer journey. Apply statistical modeling, predictive analytics, machine learning, and natural language processing (NLP) to analyze customer support conversations, transcripts, and tickets to generate actionable insights. Develop customer segmentation and clustering models to identify common customer issues and recommend targeted solutions, including self-service resources. Integrate customer feedback with transactional, operational, and behavioral data to identify key drivers of customer satisfaction and business outcomes. Design, test, and launch customer experience and support metric scorecards to track KPIs and evaluate performance across digital, AI-powered, and human-assisted sup

Who we are About Stripe Stripe, LLC. 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. What you’ll do Responsibilities Scope, design, build, and maintain APIs, services, and large-scale systems that reliably and efficiently handle billions of money movement requests; Design the next generation of Stripe products to meet the high growth needs of our company and customers; Analyze product requirements, user needs and feedback and translate them into technical specifications and determine the feasibility of design, taking into account cost and time constraints; Review API launches and library shapes for other teams to ensure that backwards and forward compatibility, coherent patterns, and extensibility meet our quality standards; Act as the team’s representative during technical meetings and understand how their systems interact with the broader landscape within the company; Mentor early-career engineers to help them grow and spin up into independent engineers; and Construct core engineering tenets and design principles for their team’s projects. Who you are Minimum requirements Master’s degree or foreign equivalent in Statistics, Data Analytics, Engineering or a related field, plus 5 years of related work experience in data science or quantitative modeling. In the alternative, the employer will accept a Bachelor’s degree or foreign equivalent in Statistics, Data Analytics, Engineering or a related field, plus 7 years of related work experience in data science or quantitative modeling, of which at least 5 years must be post-bach

About the Team The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-To-Market teams to inform high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more. We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential. About the Role We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability. This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI. 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 statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains. Own the end-to-end modeling lifecycle , including scoping, feature engineerin

Job ID: 111270 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: Responsible for influencing product roadmaps through analytics and financial and business modeling. Develop hypotheses and analytical frameworks for understanding pricing dynamics and market outcomes. Analyze collected data and extract information relevant to problems. Work closely with product leads to build efficient tools, systems, and processes to manage pricing and driver earning at scale. Develop and test quantitative models, support software, and analytical tools. Experience: Education and Experience: Master's degree or foreign equivalent in Operations Research, Analytics, or related field. 3 years of experience in job offered, analytics, or related occupation. Skills: Experience with quantitative analysis, predictive modeling, and machine learning. Experience with programming languages, analytical software, and database applications. Experience with business analytics and authoring data pipelines. Experience with optimization and programming, including C++, R, Python, and algorithms. 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, col

Job ID: 111268 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: Education and Experience: Master's degree or foreign equivalent in Business Analytics and Information Management, Data Science, or related field. 2 years of experience in job offered, operations research, or related occupation. Skills: Experience creating metrics and analytical tools to track and monitor growth. Experience with statistics, machine learning, causal inference, data scientific forecasting, and authoring data pipelines. Experience with building and evaluating optimization and inference models, and predictive modeling. Experience with writing production quality computer code and using MATLAB, R, and Python. 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

Data Engineer III itD is seeking a Data Engineer to design, build, and own the data models, pipelines, and reporting behind a large-scale robot teleoperation and wearable data collection operation at a leading global technology company, replacing manual operational reporting with automated, trustworthy systems. The ideal candidate will bring deep experience in dimensional modeling, production pipeline ownership, and distributed SQL and Python, and a track record of delivering reliable reporting infrastructure and metrics that leadership trusts. Location: Remote (US). Pay Rate: $48.60/hr Depends on Experience Duration: 12 months, full time (40 hours/week), start ASAP, with a strong possibility of extension or conversion. We provide comprehensive medical benefits, a 401k plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship. Responsibilities Design and own dimensional data models covering collection volume, operator efficiency, data quality, and equipment uptime across multiple collection methods, and build the daily and cumulative table layers that let recurring reporting be derived automatically. Define and document canonical metric definitions so key terms mean one consistent thing across dashboards, internal apps, and leadership reporting, and drive alignment when teams disagree. Build and extend batch data pipelines from operational source systems through daily snapshots to cumulative dimension tables; own correctness, freshness, and backfill of every reported metric and resolve discrepancies against source data. Build automated data-quality checks, anomaly detection, and freshness SLAs, and own backfill and restatement strategy (including communicating restatements to stakeholders) when definitions or upstream sources change. Build and own dashboards and internal reporting views, including live fleet-status views and automatically generated daily operational briefs, plus l

A Career with Point72’s Market Intelligence Team On our proprietary research team—Market Intelligence—you’ll support Analytics team members as they work with our investment professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques to alternative data sets. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our industry researchers, product managers, and data scientists and engineers work together to build compliant research products that answer the questions our investment professionals care about most. We look for other bright, motivated, and collaborative people to join our team and grow with us. About the MS/PhD Data Scientist Internship Our data scientists conduct research through data mining and statistical modeling to discover insights from large, complex data sets that are used by our investment professionals to make investment decisions. During the 10-week program based in our New York office, you will gain exposure to: A highly collegial environment that emphasizes teaching and learning as a team Tackling challenges of featuring and modeling large and unstructured data using machine learning and statistical techniques Managing all aspects of the research and execution process including methodology selection, data collection and quality, modeling and analysis, and performance monitoring Working alongside Analytics team members who deliver research findings to investment teams, portfolio managers, and other internal clients Driving technical innovation through a collaborative R&D process Summer Internship Program at Point72 In addition to the learning and development you’ll receive in your day-to-day role with your team, as a part of our summer internship program you will: Work alongside your fellow interns and be mentored

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: Partner with product owners and business groups across business units and sales. Understand their needs clearly. Turn business problems into scalable, data-driven DS, ML, AI, and GenAI solutions. Implement these solutions in Python and cloud environments. Design, develop, and implement predictive and forecasting models, machine learning models, statistical analysis, and data mining techniques to address business challenges. Design, develop, and deploy optimization and simulation models (e.g., mathematical programming, stochastic simulation, scenario analysis, and what‑if modeling) to evaluate trade‑offs, optimize business decisions, and improve operational and financial outcomes across complex, multi‑constraint problem spaces. Analyze large and complex datasets, identifying trends, patterns, and anomalies to extract valuable and actionable insights. Build and deploy data visualization dashboards and reports to effectively communicate insights to business leaders across different levels. Research and explore new data science techniques, including generative AI and large language models, to enhance business processes and decision-making. Contribute to data governance and infrastructure: Help maintain and improve our data infrastructure, ensuring data quality and integrity. Minimum Qualifications: 2+ years of experience as a Data Scientist, with expertise in using advanced analytics, machine learning, and statisti