Data Modelling Consultant Jobs

Become a part of our caring community The Lead, Infrastructure Capacity Management conducts supply/demand, trend analyses and makes proactive capacity planning recommendations to mitigate risk and rationalize the optimal amount of hardware, software and network resources to meet business needs, service level requirements and IT infrastructure growth capacity. The Lead, Infrastructure Capacity Management works on problems of diverse scope and complexity ranging from moderate to substantial. The Lead, Infrastructure Capacity Management ensures that capacity workload modeling and Performance Optimization and availability analysis is performed for a variety of platforms and environments. Serves as a subject matter expert to application development, systems administration and engineering and other technical and business staff in planning the resource requirements for systems under development. Develops, maintains, recommends, documents and supports tools and backend utilities to provide capacity planning management. Facilitates the development of policies to ensure that existing capacity is being used as efficiently as possible. Advises executives to develop functional strategies (often segment specific) on matters of significance. Exercises sound judgment and decision-making on complex issues and initiatives, working with minimal supervision. Analyzes multiple factors and business considerations to determine and implement effective solutions. Use your skills to make an impact Required Qualifications Bachelor's degree in Data Science, Data Analytics , Computer Science, Information Systems, Information Technology, Engineering, or a related technical field 8+ years of experience in cloud, and On-prem databases, infrastructure, or platform engineering. Expertise in cloud capacity planning, perfo

The Analyst – Corporate Finance is responsible for supporting financial modeling, data analysis, transaction execution, and reporting to drive strategic financial decisions. This role provides critical support in capital raising, M&A activities, financial structuring, and compliance, ensuring alignment with corporate finance objectives. Source: Adani Group | Job ID: 52880

The People Analytics Team at Datadog uses data to help our growing organization make better people decisions. We're expanding our workforce planning capabilities to support how we grow and structure our teams. In this role, you'll help build and maintain the data foundation behind our headcount and capacity models, partnering with FP&A, Recruiting, and PBPs to keep workforce planning grounded in clean, trustworthy data. At Datadog, we place value in our office culture – the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Automate and expand Datadog’s headcount-driven capacity modeling, improving the underlying data pipelines and insights that they surface Build and maintain data models covering headcount, positions, and hiring pacing, keeping them accurate as business context changes Own the position data audit process, establishing and maintaining a source of truth for open, filled, and planned positions across the business Support workforce forecasts by analyzing attrition, mobility, hiring, and promotion trends in partnership with the broader People Analytics Insights team Partner with our People Tech teams (HRIS, Recruiting Ops, developers) to shape the headcount management tech roadmap, driving for infrastructure and tooling that reduces friction and unlocks better data Serve as a point of contact for stakeholder questions on workforce planning data, handling day-to-day communications and support requests Contribute to the overall maturity of workforce planning at Datadog by improving how data is sourced, modeled, and shared Run external benchmarking analyses to inform headcount planning by researching labor market data, translating it into internal-ready insights, and publishing findings for stakeholders Who You Are: 5+ years of experience in workforce planning, people analytics, FP&A, or

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world’s most important decisions. We’re looking for an AI Product Manager to own the Finance vertical within our Agents Data & Reinforcement Learning Environments team. In this role, you’ll own both the development of RL environments (the realistic, high-fidelity simulations of financial software and workflows that labs use to train and evaluate agents) and the “data as a product” strategy that powers them. You’ll understand where AI is being used in the Finance industry, decide what financial tasks are worth modeling, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside the Finance industry, and is able to pair that domain understanding with a sense for AI research and current agent capabilities in Finance workflows. You’ll translate that expertise into environments and datasets that teach AI agents to perform real financial work, and you’ll be the domain expert Scale’s most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You’ll Do Own the Finance AI roadmap & data strategy: Set product direction for the Finance agents training stack and the data strategy behind it. Establish a vision for where AI is continuing to transform the Finance industry (including investment banking, private equity, public markets, corporate finance, FP&A, etc), driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading AI labs to understand where their Finance agentic capabilities fall short and shape new product lines and competit

Become a part of our caring community The Research Scientist 2 participates in research study design, analysis and interpretation of results, with special emphasis on statistical and analytical plan development; data acquisition, preparation, and management; statistical analysis and interpretation of findings. The Research Scientist 2 work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action. Humana’s Healthcare Quality & Reporting Improvement (HQRI) department is seeking a Research Scientist 2 to join a high-performing team dedicated to advancing predictive modeling and analytics in support of our Medicare and Medicaid business. The HQRI team plays a pivotal role within Humana, delivering insights that drive the effectiveness of risk adjustment initiatives. In this position, the Research Scientist 2 will partner with a senior research scientist to apply advanced statistical methods to rigorously evaluate the impact of risk adjustment programs and pilot projects. The findings generated will be critical in informing key business decisions and optimizing operational strategies. Additionally, the person in this role will collaborate with colleagues specializing in data science and actuarial analytics. We are seeking a candidate who brings complementary skills to the team, with the ability to learn from their teammates while contributing with their unique expertise in statistical analysis. Use your skills to make an impact Required Qualifications Bachelor's degree in Computer Science, Data Science, Mathematics or a related quantitative field; 2 years of experience applying statistical modeling, pred

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r

About the Role The Enterprise Knowledge Platform team builds the data layer that lets Perplexity's agents reach into the world's software. This team owns the systems that turn hundreds of heterogeneous integrations (native, MCP, CLI, first-party, and third-party APIs) into one unified, reliable, well-typed surface that agents can call with confidence. This platform is the core layer that forms the knowledge layer for Computer: it is how the agent discovers what tools exist, understands what each one means, decides which to call, and grounds its reasoning in real, permissioned, up-to-date enterprise data. We maintain a knowledge layer above connectors that pushes and pulls context into them, rather than letting each connector hoard org knowledge on its own, making Computer the source of truth for institutional knowledge. Models are commoditizing; grounded, actionable, permissioned access to a customer's real systems is not. When this layer is fast, accurate, and semantically rich, every agent built on top of it gets smarter; when it is weak, no amount of model quality compensates. Key Responsibilities Own the design and implementation of the connector runtime, the system that registers, hosts, and executes built-in connectors, hosted MCP servers, and CLI-backed tools behind a single agent-facing interface. Build and extend the semantic layer: tool and entity schemas, capability metadata, relationship modeling, and the mechanisms for capturing and applying organization- and account-specific corrections and knowledge. Design the tool-discovery and tool-selection surfaces that agents use to find the right connector and call it correctly, optimizing for both model accuracy and context efficiency. Make agent loops robust: structured results, partial-failure and retry semantics, idempotency, pagination, rate-limit handling, and observability into every tool call an agent makes. Define authentication, authorization, and credential-isolation patterns for connectors (OAuth fl

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined du

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Drive the global optimization and strategic evolution of Everpure’s supply chain network to ensure maximum operational efficiency, cost-effectiveness, and sustainability. In this high-impact technical leadership role, you will bridge industrial engineering rigor with data-driven decision-making, setting the analytical direction for network modeling to guide executive-level expansion and transformation plans. You will lead cross-functional initiatives across landed cost, service levels, manufacturing process capabilities, and CO2 emissions tracking while aligning closely with IT, hardware engineering, and global operations teams. WHAT YOU’LL DO Guide Network Modeling & Strategic Decision-Making: Define scenario logic, digital twin framing criteria, and tradeoff analyses for the team's Network Design Modeler, translating operational data into defensible strategies for total landed cost, service levels, CO2 emissions, and go-to-market (GTM) readiness. Assess & Level Supply Base Capability: Evaluate and align global contract manufacturers (CMs) and facilities using JDM design RFQ processes, L6/L10 manufacturing maturity, test infrastructure, and resiliency criteria to ensure site-to-site process equivalency. Drive End-to-End Supply Chain Transformation: Lead multi-workstream transformation projects from inception to closure using Agile/Scrum and Waterfall frameworks to optimize technical scope, operational bud

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As a Senior Finance Manager within our Business Unit FP&A team, you’ll play a key role in driving financial planning, forecasting, and strategic decision-making for Everpure’s subscription business. In this highly visible individual contributor role, you’ll own global top-line forecasting and financial modeling while partnering closely with Business Unit, Product, GTM, Operations, and Accounting leaders to understand performance and guide business decisions. You’ll combine deep financial expertise with a strong understanding of subscription business models to translate complex data into clear insights, strengthen how we forecast and measure the business, and help leaders make informed decisions as Everpure continues to scale. WHAT YOU'LL DO Own Global Subscription Forecasting & Financial Modeling: Lead global top-line forecasting across pipeline, bookings, revenue, and margin, while developing and maintaining P&L and capex models. Partner closely with Accounting to ensure operational forecasts align with reported financial results. Turn Business Performance Into Strategic Insights: Analyze key subscription metrics including ARR, bookings, retention, churn, expansion, and gross margin. Translate complex financial and operational data into clear insights, compelling visuals, and executive-level narratives that inform business decisions. Serve as a Strategic Finance Partner: Partner with Business Unit, Pr

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE We are seeking an EMEA Sales Finance Manager to support our EMEA Sales organization. This highly visible and commercially focused role will partner closely with EMEA Sales and Finance leadership to provide value-added financial analysis, business intelligence, and strategic insights that support business performance and go-to-market decision-making. You will analyze pipeline, bookings, deals, customer buying patterns, expenses, and other leading performance indicators , translating complex financial and operational data into clear, forward-looking narratives and forecasts. You will also partner with our Shared Services team to strengthen financial models, analytics, and reporting while driving planning, expense management, process standardization, and automation as the business scales. WHAT YOU'LL DO Commercial Finance & Business Partnership : Partner closely with EMEA Sales leadership and the Deal Desk, providing financial and commercial analysis that supports deal decisions, go-to-market strategy, resource allocation, and business growth. Reporting & Business Analytics : Analyze business trends, customer buying patterns, pipeline, deals, and market performance to deliver actionable insights that inform go-to-market strategy and measure execution effectiveness. Financial Modeling & Planning : Partner with the Shared Services team to build and maintain critical business and financial models covering he

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As Principal Pricing Strategy Manager, you will serve as the strategic architect of product pricing across Everpure’s portfolio, driving commercial growth, margin optimization, and market expansion. Operating with broad autonomy, you will integrate advanced financial modeling, competitive intelligence, and practical AI application to transform complex data into high-impact pricing frameworks. Collaborating closely with Product Management, Sales, Finance, Monetization, and Executive leadership, you will establish repeatable, data-backed monetization strategies that maximize enterprise revenue and scale pricing operations globally. WHAT YOU'LL DO Architect Strategic Pricing Frameworks : Lead portfolio-wide product pricing strategies, elasticity modeling, and SKU-level margin evaluations to optimize revenue growth and commercial competitiveness. Drive End-to-End Monetization Initiatives : Partner with Product Management, Finance, Operations, and Sales leadership to design, execute, and monitor market-aligned pricing structures and commercial policies. Pioneer AI-Enabled Pricing Operations : Integrate practical AI workflows and automated modeling techniques to accelerate scenario planning, elevate decision-making speed, and build scalable pricing processes. Lead Cross-Functional Governance & Alignment : Establish clear pricing methodology, decision frameworks, and executive materials to align senior stakeholders a

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Responsibilities and Tasks: Use knowledge of modeling, operation research, data analytics, machine learning and web application to Improve complex manufacturing operation efficiency and capabilities. Communicate effectively on approach and methodology in developing analytics, reporting solution and scheduling optimization. Demonstrate sound project management skills in requirement gathering, resource estimation, time management, stakeholders' engagement and deliverables deliveries. Collaborate effectively with team members and stakeholders both internally and externally. Participate in multi-area focus teams to improve complex constraint in manufacturing operation Possess excellent verbal and written communication skills and the ability to present project/approach/data in meetings with varying level of stakeholders. Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work. Requirements: Master’s / Bachelor’s D

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About The Role Snorkel is hiring a Head of Security to build and lead our security function end-to-end — infrastructure security, application security, and governance, risk & compliance (GRC). You'll own the security function end-to-end — strategy, team, and execution — and operate as the primary security voice with customers, auditors, and the exec team. You'll report to the CTO. This is a builder's role: you'll take security from its current state to a mature, right-sized function as Snorkel scales, hiring and developing the team as needs grow. Key Responsibilities Security Leadership & Team Building Define Snorkel's overall security strategy, goals, and roadmap across infrastructure, application, and compliance domains Build, hire, and lead a high-performing security organization — starting lean and scaling deliberately as the company and its risk surface grow Establish the operating cadence for security (metrics, reporting, incident response, risk register) and represent security posture to the executive team and board Infrastructure & Cloud Security Own cloud security architecture and posture across AWS (and other cloud providers as adopted) — IAM, network segmentation, encryption, landing zone design Direct detection & response capabilities, threat modeling, and vulnerability management programs Set standards for secure infrastructure-as-code, CI/CD, and secrets management Application Security Embed security into the product develo

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Responsibilities and Tasks: Use knowledge of modeling, operation research, data analytics, machine learning and web application to Improve complex manufacturing operation efficiency and capabilities. Communicate effectively on approach and methodology in developing analytics, reporting solution and scheduling optimization. Demonstrate sound project management skills in requirement gathering, resource estimation, time management, stakeholders' engagement and deliverables deliveries. Collaborate effectively with team members and stakeholders both internally and externally. Participate in multi-area focus teams to improve complex constraint in manufacturing operation Possess excellent verbal and written communication skills and the ability to present project/approach/data in meetings with varying level of stakeholders. Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and leg