Data Scientist

• Own assigned projects and workstreams from initiation through closeout.
• Develop and maintain project execution plans, schedules, and milestone tracking.
• Drive project progress and accountability across internal teams, vendors, consultants, and external partners.
• Coordinate project activities to ensure alignment with program objectives, timelines, and deliverables.
• Facilitate project meetings, track action items, and follow through to completion.
• Build and maintain project-level schedules aligned to the broader program master schedule.
• Monitor project dependencies and identify impacts to adjacent workstreams.
• Support integration of project schedules into the overall program plan.
• Escalate schedule risks and conflicts proactively while recommending mitigation strategies.
• Coordinate activities across engineering, design, construction, infrastructure, and operational stakeholders.
• Manage communication between project teams, vendors, consultants, and leadership.
• Ensure all parties understand scope, responsibilities, milestones, and expectations.
• Track project budgets, scope, schedules, risks, issues, and progress.
• Maintain accurate project documentation including meeting notes, decision logs, change requests, and status reports.
• Provide regular project updates and executive-ready reporting to Program Leadership.
• Identify project-level risks, constraints, and issues early.
• Drive resolution through collaboration and ownership.
• Develop mitigation plans and corrective actions when needed.
• Escalate issues appropriately while ensuring accountability remains clear.

Project Manager – Data Center Delivery

• Partner with Trade leaders to solve complex business problems using data, analytics, and quantitative decision-making
• Focus on building and productionizing Agentic AI solutions
• Translate ambiguous business questions into analytical frameworks
• Develop AI-powered tools and workflows
• Influence strategic and operational decisions
• Serve as a trusted advisor to business stakeholders
• Combine hands-on AI engineering skills, strong statistical reasoning, business acumen, and structured problem-solving to identify and act on trade insights
• Emphasize designing and deploying Agentic AI solutions via APIs
• Conduct rapid hypothesis generation, statistical analysis, experimentation, forecasting
• Communicate clear recommendations that drive measurable business outcomes

Senior Data Scientist – Health100 AI

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Data Scientist II

• Own the product roadmap for Qualitrol's Analytics as a Service portfolio.
• Prioritize features based on:
• - Customer value
• - Business impact
• - Market opportunity
• - Competitive differentiation
• - Technical feasibility
• Develop trusted relationships with early adopters and strategic customers.
• Establish structured Voice of Customer processes including:
• - Follow Me Home observations
• - Customer Advisory Boards
• - Early Adopter Councils
• - Design Partner Programs
• - Customer interviews
• - Usage analytics
• - Product telemetry
• Lead backlog prioritization and sprint planning.
• Ensure every sprint delivers measurable customer value.
• Measure product success through:
• - Customer adoption
• - Feature utilization
• - ARR growth
• - Customer retention
• - Net Revenue Retention
• - Time-to-value
• - Customer satisfaction

Product Owner – Analytics as a Service

• Lead the development and delivery of enterprise reporting, executive dashboards, KPI scorecards, portfolio analytics, competitor benchmarking, and strategic business insights.
• Conduct in-depth analysis of industry trends, competitive dynamics, emerging technologies, market opportunities, and regulatory developments affecting the consumer lending, credit card, banking, payments, and fintech industries.
• Apply advanced statistical techniques, machine learning models, and predictive analytics to identify patterns, forecast market changes, and support strategic business decisions.
• Design and implement AI-powered market intelligence and competitive research solutions that automate the collection, synthesis, and interpretation of market data.
• Utilize Large Language Models (LLMs) to analyze and summarize earnings calls, SEC filings, analyst reports, press releases, industry publications, and competitor disclosures.
• Develop Retrieval-Augmented Generation (RAG) solutions and AI agents that enable continuous monitoring of competitor activity, customer trends, market signals, and regulatory developments.
• Build executive AI copilots that support strategic planning, competitive analysis, and business decision-making.
• Integrate external market, economic, customer, and industry datasets with internal business performance data to generate comprehensive insights.
• Analyze portfolio performance across lending products, identifying opportunities related to growth, profitability, customer behavior, risk management, and operational efficiency.
• Partner with business, product, marketing, digital, risk, technology, and finance leaders to translate analytical findings into actionable business recommendations.
• Support board presentations, regulatory requests, audit reviews, second-line risk reviews, and executive strategic initiatives through rigorous analysis and communication.
• Prepare audit-ready analyses and documentation to support regulatory, compliance, and governance requirements.
• Present complex analytical findings and strategic recommendations to executive leadership in a clear, concise, and compelling manner.
• Foster a culture of innovation, analytics excellence, data-driven decision-making, and AI adoption across the organization.

Director, Data Science

• Own and lead Vendelux's analytics strategy end to end: measurement frameworks, metric definitions, reporting standards, and our agentic analytics platform.
• Mentor and grow a high-performing analytics team responsible for delivering insights that shape product strategy and roadmap decisions.
• Partner with cross-functional leaders and executives to define and monitor core company metrics and prioritize initiatives based on measurable customer and business impact.
• Own the forecast and insights into drivers of company and product performance.
• Lead and conduct deep-dive analyses of how customers use event intelligence – eg data coverage, campaign conversion, ROI measurement – to surface product and growth opportunities and inform the roadmap.
• Partner with Engineering teams to build and continuously improve the semantic layer underlying the agentic analytics platform, tighten metric governance, and expand governed self-serve analytics.

Head of Analytics

• Lead the strategy, development roadmap, and lifecycle of data products and platforms
• Define the roadmap for data solutions
• Collaborate with cross-functional teams
• Ensure data products are scalable, reliable, and user-friendly
• Monitor and improve data quality, reliability, and user adoption of data tools
• Define and track success metrics for data products

Staff Data Product Manager

• Manages a small team of data scientists and data engineers to research, design, develop, deploy, and maintain machine learning, AI, and agentic AI solutions supporting the Claims organization.
• Communicates project progress, insights, results, and recommendations to business partners and senior leadership.
• Manages project scope, expectations, and timelines.
• Collaborates with Data Engineering, IT, and business partners to operationalize machine learning and AI solutions.
• Follows the model governance process including planning, documentation, validation, deployment, monitoring, and review.
• Oversees model performance and supports ongoing monitoring and continuous improvement of deployed solutions.
• Develops and mentors team members to maintain technical excellence in AI/ML, software engineering, and solution design.

Data Science Manager

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
• Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

Senior Associate, Data Scientist – Bureau Data Strategy

• Steward and evolve the services data schema & taxonomy.
• Own and iterate the curation pipeline. Sourcing, screening, and tagging.
• Direct a small bench of data specialists.
• Work at the nexus of design, product, engineering, and service partners.
• Advise on internal tooling.
• Document the playbook.

Services Data Lead

• Translate complex business problems into coherent, actionable quantitative solutions
• Work closely with stakeholders to deeply understand their needs and deliver clear and actionable insights
• Build statistical models that will decipher the impact of key decisions and the impact of competitor’s decisions
• Forecast the future of our DTC businesses
• Measure the price elasticity of our DTC products and competitive products across global and domestic markets
• Develop a coherent and optimized pricing strategy across our DTC products
• Contribute to models advancing Paramount’s DTC financial forecasts
• Integrate data science tooling into all aspects of our DTC financial forecasts

Senior Data Scientist

• Apply your expertise in quantitative analysis, data mining, and statistical modeling to deliver impactful, objective, and actionable data insights that enable informed business and product decisions
• Drive informed and timely decision-making that improves and optimizes the way our products are created, executed, and adopted
• Collaborate with product managers, engineers, product marketers, and designers
• Think creatively, proactively, and futuristically to identify and size up new opportunities within Snap's long-term roadmap for data-scientific contributions
• Conduct machine learning or statistical analyses, and build pragmatic, scalable, and statistically rigorous solutions to deliver actionable insights, accurate predictions, and effective optimizations
• Communicate best practices in quantitative analysis and develop cross-functional partnerships
• Utilize AI tools to more efficiently develop scalable data solutions, while maintaining rigorous standards for accuracy and statistical integrity.

Senior Data Scientist, Level 5

• Define an AI vision and multi‑year roadmap
• Build and manage an AI use‑case portfolio
• Lead discovery and delivery of solutions
• Navigate governance and controls
• Partner across platform teams
• Champion Responsible AI
• Drive change management
• Track and report outcomes

Vice President, Data Transfer, Integration & Quality Manager

• Evaluate open-source and internally-developed modeling and analytics tools using real business data
• Integrate internal data with external data sources and APIs to discover and implement actionable insights
• Design and craft data science models to communicate solutions to customers and company leadership

Data Science Intern

• Working closely with practice group leadership and team members in both Professional Development and Legal Talent, the Associate Development Manager is primarily responsible for supporting associate staffing, utilization, integration and development.
• Work with practice group leaders and partners in charge of staffing to manage the work allocation process for associates in the group
• Monitor workloads and professional development of associates and help allocate new matters in a manner which ensures an equitable distribution of assignments consistent with the clients’ needs and the attorneys’ individual professional development goals
• Track, aggregate and analyze associate metrics, including availability information and utilization rates.
• Partner with practice group leaders and associates to ensure that individual goals relating to productivity are achieved and practice group productivity is maintained
• Coordinate with practice group leaders and other supervising partners to identify staffing needs and hiring targets; partner with the Legal Talent team to ensure hiring efforts are supporting the goals and needs of the group
• Support the associate performance review process by working with practice group leaders and Associate Review Committee members to ensure quality reviews are delivered in a timely fashion
• Help monitor associate evaluations, prepare review delivery scripts and facilitate the delivery of formal reviews.
• Work with associates to implement feedback received, collaborating with Professional Development team members to provide coaching, where necessary
• Meet regularly with practice group leaders to identify high performing associates and associates who may be having specific challenges so that appropriate mentoring, training and other actions can be taken to address specific circumstances in a timely manner.
• Facilitate frequent feedback between partners and associates
• Partner with Legal Talent and other internal administrative departments to facilitate successful attorney on-boarding and integration, including conducting department orientation for new hires and building robust onboarding schedules.
• Help conduct exit interviews such that the firm can leverage departing associate feedback to improve the associate experience
• Collaborate with Professional Development and Legal Education team members to develop, enhance and implement legal and professional skills training programs and initiatives to support associate development
• Collaborate with the firm’s Attorney Licensing and Compliance team members to ensure associates obtain and maintain their licensure requirements and engage in continuing legal education aligned with development goals
• Collaborate with the firm's Diversity and Inclusion team to champion and implement initiatives and events.
• Promote best practices in commitment to an inclusive culture and serve as a resource for diverse attorneys
• Collaborate with HR/Wellness teams to promote the wellness of associates
• All other duties as assigned or required

Associate Development Manager – Cyber, Data, Privacy Group

• Manage strategic relationships with public power partners
• Identify growth opportunities in competitive retail markets and bilateral utility arrangements
• Originate and advance data center infrastructure opportunities with key customers and support customer-facing initiatives
• Participate in the development and delivery of customer proposal presentations
• Coordinate large load registrations, energy management optimization, participate in demand response programs, and develop risk reduction strategies with Structured Trading and Market Operations
• Manage private use networks (PUN) in ERCOT, owning QSE relationships, ensure compliance, and collaborate across teams to optimize energy use for data centers
• Stay up to date on energy regulations, advise on compliance across markets, and build relationships with utilities and regulators in coordination with internal teams
• Support the structuring and execution of retail supply agreements and long-term contracts
• Work with the broader team to prepare internal materials for approvals

Senior Manager, Data Center Infrastructure Origination

• Champion AI-ready data products by ensuring trusted business definitions, semantic consistency, metadata, lineage, observability, documentation, and governance are embedded into every streaming and social data product.
• Ensure data products are designed to support emerging AI capabilities—including semantic retrieval, recommendation systems, intelligent agents, and LLM-powered experiences—through high-quality, well-governed enterprise data.
• Partner with Commercial Strategy, Global Insights, Label Analytics, Marketing, Finance, and Digital Business teams to define trusted business metrics, KPIs, and standardized consumption definitions.
• Manage the lifecycle of external consumption data sources, ensuring licensed datasets are consistently ingested, governed, documented, monitored, and integrated into trusted enterprise data products.
• Define scalable dimensional models and semantic layers supporting streaming activity, audience engagement, artists, releases, tracks, playlists, social engagement, territories, and commercial performance.
• Establish authoritative data products that serve as the source of truth for music consumption performance across labels, artists, releases, and markets.
• Standardize business definitions for metrics, including streams, listeners, followers, saves, playlist reach, engagement, audience growth, chart performance, market share, and consumption trends.
• Partner with engineering teams to implement SLAs, monitoring, observability, incident management, and operational support processes.
• Establish and maintain data contracts with internal and external consumption data providers to improve reliability and predictability.
• Drive adoption of consumption data products through business-friendly documentation, semantic models, stakeholder enablement, and training.
• Evaluate opportunities to improve business outcomes by applying AI to music consumption, audience behavior, and content performance while maintaining strong governance and data quality standards.

Senior Manager, Data Product – Streaming, Social

Senior Manager, Data Center Infra Origination

• Ensure the scientific coherence of Tempus’ multimodal data platform
• Bridge the gap between complex molecular science and scalable data engineering.
• Conduct rigorous data evaluations, write technical code (SQL, R, Python), and prototype new data offerings.
• Deliver implementation-ready table and column specifications to seamlessly transition initial concepts into scalable, production-grade offerings.
• Translate complex client research objectives across drug discovery and development lifecycle into actionable clinico-genomic data strategies.
• Ensure seamless alignment between client hypotheses and Tempus capabilities.
• Evaluate datasets, perform User Acceptance Testing (UAT), and build data insight reports.
• Support the continuous growth and scaling of Tempus' expanding clinical-genomic footprint across diverse disease domains.

Principal Scientist – Data Insights, Hypothesis Design

• Responsible for mining big data, interpreting and analyzing complex data sets
• Develops and deploys predictive models to analyze company performance and improve customer experiences
• Applies statistical techniques and machine learning algorithms to identify trends within Mazda data
• Collaborates closely with data engineers, analysts, and business stakeholders to integrate data-driven solutions

Data Scientist jobs in New York

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