Senior Data Modelling Dataverse Jobs

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will lead the design and development of core ML models that power Instacart’s ads ecosystem. This is a research-leaning role focused on theoretical problem formulation, training methodology, and model quality rather than infrastructure or full-stack engineering. You will tackle fundamental challenges in pCTR modeling such as mitigating selection bias, position bias, and optimizer’s curse in training data, improving model calibration across surfaces and domains, and advancing our multi-task learning and sequence modeling capabilities. You will also have the opportunity to shape our next-generation foundation model approach for ads ranking and contribute to cutting-edge retrieval systems like TIGER (Transformer Index for Generative Recommenders), Semantic ID and domain language

Senior Low Observables (LO) Mission Systems Integration Engineer Company: The Boeing Company The Senior LO Mission Systems Integration Engineer will lead design, integration, analysis, test, and production activities for low observable materials, structures, apertures, sensors, and radomes for mission systems. The role requires strong technical leadership, independent execution of complex tasks, advanced use of computational electromagnetic (CEM) solvers, and the ability to produce and defend technical results with minimal oversight. Key Responsibilities Lead design, modeling, and analysis efforts for LO materials, coatings, structures, and integrated mission systems to meet signature reduction and performance requirements. Independently apply CEM solvers (e.g., FEKO, HFSS, CST, WIPL‑D, xFDTD, or equivalent) to model antennas, apertures, radomes, and LO treatments; perform design optimization and trade studies. Drive integration of LO treatments with mechanical, thermal, and sensor/antenna system constraints; identify and mitigate producibility, testability, and sustainment risks. Plan, execute, and oversee laboratory and field tests (anechoic chamber measurements, antenna/radome characterization, RCS measurements); lead data collection, reduction, and validation activities. Develop and validate predictive models, reconcile simulations with measurements, perform uncertainty quantification, and provide actionable recommendations to engineering and program leadership. Produce high-quality technical documentation: test plans, test reports, technical memoranda, design reviews, and customer briefings. Mentor and provide technical oversight to junior engineers and technicians; ensure adherence to engineering processes, qual

Who We Are At MongoDB, we are building the future of data platforms with MongoDB Atlas; our fully managed, multi-cloud database service. The Infrastructure Security (InfraSec) team sits within Site Reliability Engineering (SRE) in the CTO organization. We are an engineering team dedicated to building the security infrastructure, primitives, and reusable controls that protect MongoDB Atlas across AWS, Azure, and Google Cloud (GCP). InfraSec operates on a preventative, enabling model: rather than acting as a manual approval gatekeeper or compliance auditor, we develop automated guardrails and platform capabilities. We integrate security directly into the platform runtime, CI/CD, and Infrastructure-as-Code (IaC) workflows so engineering teams can operate securely at scale without friction. This role can be based out of our New York City office or remotely in the eastern or central timezone. What You’ll Do Harden hosts and containerized workloads using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups) and eBPF-based tooling (Cilium, Tetragon) Secure containerized infrastructure across multi-cloud environments via RBAC, network policies, admission controls (Gatekeeper), and runtime threat detection. Build and manage automated services for Cloud Security Posture Management (CSPM), workload identity, vulnerability management, and access controls across AWS, Azure, and GCP Write production-quality code and leverage Infrastructure-as-Code (Terraform) to version, test, and deploy security controls as code Build real-time security monitoring, logging, and alerting systems to detect anomalies and track security posture at Atlas scale Lead initiatives across their full lifecycle; from threat modeling and architectural design to implementation, rollout, and long-term production reliability What We’re Looking For Minimum Qualifications: 5+ years in SRE, Infrastructure Engineering, or Cloud Security Engineering Strong coding skills in Go (Golang), Python, C, C++, or R

Who We Are At MongoDB, we are building the future of data platforms with MongoDB Atlas; our fully managed, multi-cloud database service. The Infrastructure Security (InfraSec) team sits within Site Reliability Engineering (SRE) in the CTO organization. We are an engineering team dedicated to building the security infrastructure, primitives, and reusable controls that protect MongoDB Atlas across AWS, Azure, and Google Cloud (GCP). InfraSec operates on a preventative, enabling model: rather than acting as a manual approval gatekeeper or compliance auditor, we develop automated guardrails and platform capabilities. We integrate security directly into the platform runtime, CI/CD, and Infrastructure-as-Code (IaC) workflows so engineering teams can operate securely at scale without friction. This role can be based out of our New York City office or remotely in the eastern or central timezone. What You’ll Do Harden hosts and containerized workloads using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups) and eBPF-based tooling (Cilium, Tetragon) Secure containerized infrastructure across multi-cloud environments via RBAC, network policies, admission controls (Gatekeeper), and runtime threat detection. Build and manage automated services for Cloud Security Posture Management (CSPM), workload identity, vulnerability management, and access controls across AWS, Azure, and GCP Write production-quality code and leverage Infrastructure-as-Code (Terraform) to version, test, and deploy security controls as code Build real-time security monitoring, logging, and alerting systems to detect anomalies and track security posture at Atlas scale Lead initiatives across their full lifecycle; from threat modeling and architectural design to implementation, rollout, and long-term production reliability What We’re Looking For Minimum Qualifications: 5+ years in SRE, Infrastructure Engineering, or Cloud Security Engineering Strong coding skills in Go (Golang), Python, C, C++, or R

We at NVIDIA seek an Senior Developer Relations, Automated Synthetic Chemistry Science Lead who can coordinate science streams. This role exists at the crossroads of experimental science, optimization, analytical characterization, AI modeling, laboratory automation, and data infrastructure. It demands a practitioner with a background in research who can lead interdisciplinary science teams and accelerate experimentation without compromising scientific quality. What you'll be doing: Coordinate the operating plan across research priorities, technical execution, and program achievements. Convert research objectives into experimental priorities, parameter-space development, campaign planning, and success criteria. Lead research initiatives encompassing synthetic chemistry, catalysis, process chemistry, machine learning, automated systems, and data processing. Build standardized experimental traces capturing successful and unsuccessful outcomes, metadata, quality-control signals, analytical summaries. Guide AI systems for feasibility assessment, outcome prediction, optimization, scope exploration, and campaign orchestration. Integrate automated experimentation, analytical data streams, data curation, model retraining, and campaign decisions into a closed-loop operating model. Establish science-stream governance: build reviews, decision logs, risk and dependency tracking, quality thresholds, and paths for addressing blocking issues. Prepare recurring workstream readouts for program leadership, including scientific progress, critical decisions, cross-team dependencies, resource needs, and unresolved risks. What we need to see: PhD (or equivalent experience) with 10+ years of hands-on experience in experimental science, chemical engineering, material science, robotics, a

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the role As the Senior Analyst, Total Rewards (Data Insights & Modeling), you will be a strategic partner reporting directly to the SVP, Total Rewards. You will bridge the gap between complex data science and talent strategy, serving as a lead architect for our global compensation structures. You will go beyond traditional reporting to build and maintain the predictive models that forecast salary market movement, simulate compensation cycles, and drive pay equity outcomes. This position is pivotal in ensuring our compensation practices remain fair, equitable, and market-relevant, directly supporting our ability to attract and retain the world-class talent necessary to sustain The New York Times’s journalistic mission. Responsibilities Strategize design and maintenance of global compensation structures using advanced data science and predictive analytics. Develop sophisticated models for variable pay (AIP/LTI) and annual merit/bonus cycles under various business performance scenarios. Build predictive models to forecast salary market movement and internal budget requirements. Conduct statistically significant pay equity analyses to identify and remediate gaps across demographics. Build and maintain automated Total Rewards benchmarking tools and executive dashboards. Lead the advancement of data insight capabilities to support compensation analytics for the New York Times workforce. Manage participation in external compensation

RDQ127R59 Summary As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will span the entire stack—from cluster management down to query compilation. You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers. Impact You Will Have Accelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques. Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support Shape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks. Drive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency. Scale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale Innovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments. Minimum Qualifications Education: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc). ML Experience: Strong background in building, training, and deploying machine learning models in production. Infrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks. Core Coding: Proficiency in Python, Scala, or Java. Preferred Skills Advanced Education: PhD in AI, Data Science, or a related technical discipline. Industry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment. Systems Domain:

Opportunity Overview: We are seeking a Financial Analyst to join our FP&A team. This is a hands-on, detail-oriented role embedded within our Commercial organization. The right candidate brings sharp analytical instincts, a bias for action, and the ability to deliver reliable financial support at a pace that keeps up with a fast-moving sales team and pricing leader What you’ll do: Develop, maintain, and utilize pricing models to forecast profitability, revenue impact, and margin changes Analyze the cost impact of process and product improvements, incorporating them into financial and pricing models Partner with Commercial, Clinical/Operations, and Actuarial teams to develop comprehensive pricing models and present strategic summaries to executive leadership Review and approve deal opportunities, RFP responses, custom pricing structures, and discounting frameworks Gather and compile data points from internal systems to monitor financial performance, metrics, and client profiles Assist with organization-wide strategic projects and provide scenario modeling, serving as the subject matter expert for pricing strategy and inputs Support budget and forecast preparation for the sales and marketing organizations — partnering with the team to build credible, data-backed plans Utilize Adaptive Insights (Workday Adaptive Planning) to manage planning cycles, scenario modeling, and financial reporting with efficiency and accuracy Apply AI-powered analytics tools to automate routine tasks, surface insights faster, and continuously elevate the quality of financial outputs ISMS roles and responsibilities Fair understanding of Information Security practices. Align to the organization policies and procedures. Ensure to get updated with ISMS roles as assigned by the department/process heads. Required Qualifications: Must-haves 3–6 years of pricing, commercial finance, or operations finance experience; healthcare, BPO, or technology-enabled services industry background preferred Adva

Opportunity Overview: As a Staff Data Scientist at Cohere Health, you will serve as a technical leader across high-priority initiatives, shaping how data science is applied to some of the most complex challenges in healthcare. You’ll drive the design of advanced analytical and modeling solutions, influence strategic direction, and partner deeply across Product, Clinical, and Engineering to deliver scalable, high-impact outcomes. This role goes beyond execution. You’ll define approaches, set standards, and guide others in solving ambiguous, high-leverage problems. You’ll play a critical role in advancing the maturity of data science at Cohere while contributing directly to improving clinical and operational decision-making. What you’ll do: Lead the design and execution of complex, high-impact data science initiatives across multiple domains Define analytical frameworks and modeling approaches for ambiguous, strategic problem spaces Partner with senior stakeholders to shape problem definition, prioritize opportunities, and influence decision-making Develop and deploy advanced models and scalable analytical solutions that drive measurable outcomes Establish best practices for experimentation, model development, and analytical rigor across the team Mentor and guide other data scientists, providing technical leadership and elevating team capabilities Drive cross-functional alignment to ensure solutions are practical, scalable, and integrated into workflows ISMS roles and responsibilities: Good knowledge of Information security Oversee specific business processes within the ISMS. Responsible to manage the ISMS documentation, conduct risk assessments, and implement risk treatment plans. Risk Owners are responsible for identifying, assessing, and managing risks within their areas of responsibility. They are also responsible for implementing risk treatment plans. Conduct the BCP and other test related to information security continuity along with CISO Responsible for monitor

P-1443 At Databricks, we’re passionate about enabling data teams to solve the world’s toughest problems — from accelerating medical breakthroughs to building the next generation of intelligent products. We do this by creating the world’s best Data Intelligence Platform , empowering customers to turn massive data into deep, actionable insights. Founded by engineers and driven by innovation, we’re obsessed with designing intuitive, high-performance user experiences that make complex data exploration simple and approachable. As a Senior Frontend Engineer focused on Dashboards , you’ll build intuitive and scalable end-to-end experiences that help users create, explore, and share insights from data. You’ll work across the frontend, partnering with designers, product managers, and engineers to develop the next generation of dashboards, interactivity, and analytical workflows within Databricks. What You’ll Do Design and build intuitive, high-performance experiences for creating and editing dashboards, as well as for authoring the data behind them, including SQL datasets, custom calculations, and semantic modeling. Partner closely with design and product to translate complex analytical concepts into polished, intuitive, and efficient dashboard experiences. Drive innovation in how Databricks users interact with data, enabling seamless and responsive exploration at scale. Own frontend development for core dashboard workflows, with a focus on usability, performance, accessibility, and reliability. Help shape the architecture, abstractions, and platform foundations that support a broad range of dashboarding and analytical use cases. Collaborate with backend engineers and adjacent teams to define APIs, data models, and contracts that power interactive and scalable dashboard experiences. What We Look For 5+ years of professional software engineering experience, with strong experience building both frontend and backend systems. Expertise in modern frontend development with HTML, C

Do you have an insatiable curiosity and passion for science? Do you want to partner with PIs at the top research institutions in the world to accelerate their life's work? We are seeking a dedicated and science-savvy Senior Account Manager to lead our relationships with a few key R1 universities in the Northeastern or Mid-Atlantic regions. NVIDIA’s accelerated computing platform is the scientific instrument transitioning research from traditional sequential computing to massively parallel, neural networks driven labs. Our full-stack platform includes supercomputers, the CUDA programming model, and hundreds of libraries, frameworks, and models. From BioNeMo for structural biology, Parabricks for genomics, Omniverse for 3D virtual worlds, and RAPIDS for data science, to CUDA-Q for hybrid quantum-classical computing, PhysicsNeMo for physics-informed AI, and Earth-2 for climate modeling, we are empowering the next scientific breakthroughs. What You'll Be Doing: Institution and Government Engagement: Serve as a trusted advisor to university and occasionally, state government leaders, communicating NVIDIA's vision, technology roadmaps, and research impact. Grow the Business: Champion organic business growth, forecast revenue, and collaborate with IT and business partners on go-to-market strategies. Research Community Partnership: Forge strong connections with leading research labs and PIs across diverse scientific domains (e.g., AI/ML, life sciences, physical sciences, climate science, engineering, and materials science). You will understand their grand challenges and keep a pulse on emerging computational methods. Strategy Execution: Engage internal cross-functional NVIDIA teams (Solution Architects, Developer Relations, Product Management, Business Units, etc.) and university partners to accelerate science on NVIDIA’s platform. Ecosystem Enablement &

(GAQ427R230) About the role As customers build their mission-critical data and AI workloads on Databricks, our shared cloud platform infrastructure is scaling at unprecedented speed. We are looking for a Product Finance Senior Manager to own the economics and financial operations of our multi-cloud platform spend. You will be a key finance partner to our Cloud Engineering and Infrastructure Operations leaders, with a mandate that spans driver-based cloud forecasting, infrastructure efficiency roadmaps, and scalable cost attribution across our product portfolio. The impact you will have Drive analytics and modeling to understand how platform spend scales Lead deep data analytics to identify the underlying drivers of shared cloud platform spend across products, cloud providers, and global regions. Build robust, driver-based forecasting models that accurately predict infrastructure spend across regional expansion, customer scale, and new product launches. Partner with Cloud Infrastructure Operations to design a forward-looking cost attribution model that accurately maps shared platform expenses to individual products. Establish robust KPIs and operations to achieve unit economics goals Partner with Engineering to define north star efficiency KPIs across core platform services and storage/compute layers. Build the infrastructure efficiency roadmap alongside Engineering and translate technical optimizations into committed operating and gross margin targets. Drive tight operational rhythms and reporting so product and engineering leaders have clear visibility to execute against their unit economic goals. Scale cloud finance operations and systems Bring systems-level thinking to cloud FP&A processes, building automated workflows that scale as our multi-cloud footprint and commitment structures become increasingly dynamic. Ensure cloud cost allocation frameworks, monthly accruals, and reporting pipelines remain rigorous, auditable, and scalable as the business co

About Stitch Fix, Inc. Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential. About the Role At Stitch Fix, we are at the forefront of innovation, creating cutting-edge solutions that blend fashion, technology, and data science. Our data science team combines machine learning with expert human judgment to generate innovative recommendations and insights that transform the way our clients discover what they love. We believe in a curiosity-driven data science culture where members are empowered to deliver impact through end-to-end model development. The diversity of the problems we work on and the data-rich environment of our business make it possible and essential to bring the tools of multiple disciplines to bear on our hardest problems. We are looking for an experienced team manager for Growth Algorithms to lead a talented group of data scientists responsible for optimizing client acquisition, retention, and reactivation. The team works across the client lifecycle—from paid media and onboarding to site experiences, CRM, incentives, and reactivation—using experimentation, predictive modeling, and personalized recommendations to help clients discover value and build lasting relationships with Stitch Fix. This is a highly cross-functional leadership role. This leader will bring a compelling data science vision that gives the team focus and inspires partners, while building trusted relationships across Product, Marketing, Engineering, Finance, Design, Enterprise Analytics, and other Algorithms teams. This leader will emphasize technical excellence while influencing business strategy, im

As a Senior Security Engineer within Application Security at Datadog, you will help secure emerging application architectures where established security patterns may not yet exist, including agentic applications, LLM-enabled products, protocol-driven tool use, and untrusted execution environments. You will establish and validate security models, requirements, and controls while partnering with product and platform teams to develop secure-by-default approaches. Your work will address evolving trust boundaries, agent identity, data access, tool permissions, and runtime behavior through threat modeling, security solutions, and practical implementation. You will have the opportunity to shape how Datadog safely supports new application paradigms and address emerging security risks before they become systemic. 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: Define security models, requirements, and guardrails for emerging application architectures where established patterns are incomplete or do not yet exist. Design, implement, and validate practical security controls that reduce risk in emerging architectures and high-risk system behaviors. Shape how emerging systems authenticate, authorize actions, isolate workloads, and access data, applying least-privilege principles throughout. Partner with product, platform, Infrastructure Security, and other engineering teams to identify security gaps and embed secure-by-default requirements from early design through production. Lead threat modeling and security assessments for new and existing products, focusing on evolving threats, unfamiliar trust boundaries, and new interaction patterns. Prioritize and drive remediation of emerging security risks, including continuous security testing where it provides durable cover

The Compensation team serves as a strategic advisor to business leaders, managers, and employees across MDB. We use data and insights to drive value and build the tools, models, and frameworks that support sound compensation decisions. This role sits within Compensation and partners closely with the Sales organization —and with Recruiting, Finance, Sales Operations, Legal, and HR. The Difference You Will Make We are looking for a Senior Compensation Partner to serve as the dedicated compensation partner for the Sales organization. This role will support VP and Director-level leaders, and their HRBP partners as the primary day-to-day compensation resource. The ideal candidate will be a trusted business partner and builder of compensation programs, tools, and frameworks. They will bring deep experience supporting Sales organizations, a strong understanding of incentive plans, and the ability to partner effectively with Sales Operations and other teams that design them. This person must be comfortable operating autonomously, influencing senior stakeholders, and navigating a fast-moving environment. A Typical Day Serve as the dedicated compensation partner for the Sales organization, supporting leaders and People Partners across Sales Provide data-informed guidance on new-hire offers, internal equity, leveling, promotions, retention actions, and out-of-cycle requests Build a strong understanding of Sales incentive plans and partner with the teams that design them to assess effectiveness and support informed compensation decisions Own Sales compensation-cycle execution end-to-end, including market benchmarking, budget modeling, manager enablement, and leadership rollups Lead competitive intelligence for Sales roles, researching compensation trends, pay practices, incentive structures, and talent movement in the evolving technology and AI landscape Supplement survey data with recruiting signals, offer data, sales talent trends, and other real-time market sources Partner w