Data Scientist

• Design and build pipelines to collect supplier data and chemical product information (specifications, CAS numbers, certifications, SDS/regulatory documents, NAICS classification of manufacturing plants) from supplier sites, distributor catalogs, trade databases, and other public and semi-structured sources
• Develop and maintain web scrapers and automated ETL workflows to keep supplier and product data current at scale
• Clean, normalize, and reconcile inconsistent supplier data into structured, standardized formats suitable for internal tools and analytics
• Apply chemical domain knowledge to validate and enrich data — resolving product names, CAS numbers, synonyms, and specifications across suppliers
• Evaluate and improve matching and classification models to map suppliers and products to buyer requirements, and to identify overlapping or equivalent chemical offerings
• Partner with Supplier Management and Engineering to define data quality standards, identify gaps in supplier coverage, and prioritize new data sources.
• Own pipeline health and data quality, and drive the KPIs that measure overall data coverage

Chemical Data Scientist

• Serve as lead for programming, analytics, and statistics when working collaboratively with teams of health services researchers and business analysts to draw insight and intelligence from large administrative claims datasets, electronic medical records and various healthcare registry datasets.
• Identify and develop solutions that can be implemented to key strategic business problems using high-level modeling and statistical analyses techniques.
• Utilize SQL to perform advanced-level data extraction, transformation and data management; fully document and manage library of source code and algorithms for future use.
• Identify, develop and test hypotheses in support of research and product offerings, and communicate findings in a clear, precise, and actionable manner to our clients.
• Respond to and lead highly complex operational data requests and create ad-hoc queries to support research projects.
• Provide quality control, quality assurance and review for projects where not the lead including solution orientated approaches and mentoring for cross functional training across the functional project teams.
• Serve as lead when working closely with Inovalon’s Enterprise Data Management, Data Integration, MORE2 Registry®, and iPORT+™ teams to identify, understand, and resolve data issues and improve the efficiency, productivity and scalability of Avalere and Inovalon Product and production data processes.
• Troubleshoot complex production-related issues and coordinate successful resolution.
• Assist with the evaluation of data analytic vendors and tools.
• Maintain compliance with Inovalon’s policies, procedures and mission statement.
• Adhere to all confidentiality and HIPAA requirements as outlined within Inovalon’s Operating Policies and Procedures in all ways and at all times with respect to any aspect of the data handled or services rendered in the undertaking of the position.
• Fulfill those responsibilities and/or duties that may be reasonably provided by Inovalon for the purpose of achieving operational and financial success of the Company.
• Uphold responsibilities relative to the separation of duties for applicable processes and procedures within your job function.
• We reserve the right to change this job description from time to time as business needs dictate and will provide notice of such.

Principal Health Data Scientist

• Own the end-to-end development and deployment of agentic LLM applications that deliver measurable business impact.
• Design, build, evaluate, and ship production-ready AI systems from prototype to production.
• Partner with founders to define product direction and turn business problems into AI solutions.
• Collaborate with Engineering to build scalable AI infrastructure, system architecture, and internal tools.
• Improve system performance, reliability, and user experience through rapid experimentation and iteration.

AI & Data Science – LLMs, Healthcare Insights

• Own retailer onboarding from kickoff through go-live.
• Manage weekly scan data submission health across the full retailer base.
• Serve as the primary point of contact for all retailer and CPG partner communications.
• Publish the weekly health dashboard for program performance.
• Coordinate with Scan Data Engineering to ensure technical setup and test submissions are completed.
• Monitor each submission cycle and communicate directly with retailers on action items.

Data Programs Manager

• Design and run the experimentation engine for fundraising actions.
• Build predictive and forecasting models that drive donor lifetime value and retention.
• Own model quality and evaluation for trustworthy AI products.
• Manage ML lifecycle on Databricks and MLflow including model training and performance monitoring.
• Define technical direction for data science with high standards and rigor.
• Partner daily with data engineers and AI engineers.

Lead Data Scientist

• Applies data science and machine learning to the analysis of electrical, vibration, and acoustic signals, transforming raw time-series sensor data into actionable diagnostics and predictive insights for rotating industrial equipment.
• Partners with engineering and domain experts to design and deploy production-grade signal processing and ML solutions for predictive maintenance across industrial applications.
• Operates effectively in ambiguous problem spaces where signal quality, environmental noise, and domain constraints require both technical rigor and adaptive thinking.
• Design and develop signal processing pipelines and machine learning models that operate on electrical (current/voltage), vibration, and acoustic time-series sensor data, including symmetrical component analysis, matched filtering, wavelet decomposition, and time-frequency analysis techniques.
• Evaluate algorithm performance using both objective metrics and subjective measures, including integration with speech recognition engines where applicable.
• Perform exploratory data analysis, feature engineering, and signal feature extraction on raw electrical, vibration, and acoustic data to surface fault patterns and anomalies.
• Analyze and interpret signals from electrical asset monitoring systems (motors, generators, pumps) utilizing electrical signature analysis, vibration analysis, and signal processing expertise to support fault isolation and anomaly detection.
• Use cross-sensor asset monitoring data (temperature, speed, load) to characterize and validate signal-derived diagnostics.
• Apply data-driven signal processing methods to characterize and isolate faults at the subsystem, component, and machine level, identifying root causes from spectral, electrical, and vibration sensor data in rotating industrial equipment.
• Contribute to end-to-end ML workflows including data ingestion, model training, inference, and monitoring for drift and degradation in live environments.
• Collaborate with engineering, product, and domain SMEs to translate operational challenges into well-scoped data science solutions.
• Communicate findings, model performance, and business value clearly through visualizations, written documentation, and presentations to technical and non-technical stakeholders.
• Explore and evaluate emerging signal processing and AI techniques, recommending production incorporation where appropriate.

Data Scientist – Predictive Maintenance

• Be a hands-on scientific and technical leader, leading a portfolio of RWE projects, developing best practices, and mentoring team members.
• Identify common technical requirements for RWE projects, develop and maintain a common suite of tools that enable RWE data scientists to accelerate project delivery.
• End-to-end expertise in RWE studies including conceptualizing research questions, data feasibility, study design, analysis, programming, and interpretation.
• Provide thought leadership and hands-on programming expertise for developing and applying Real-World Data (“RWD”) methodologies to mitigate observed and unobserved biases in the execution of external control arm studies, hybrid control studies, comparative effectiveness analyses, etc.
• Provide thought leadership and hands-on programming expertise to generate actionable insights from post-hoc RCT analyses, observational databases, and literature reviews to support regulatory agency interactions.
• Independently create study protocols, statistical analysis plans, and statistical programming deliverables including analysis-ready data, tables and figures
• Partner with the Data Science Therapeutic Area scientists to conceptualize, lead, shape and deliver Real World Evidence

Senior Principal Scientist, Data Science RWE

• Lead operational planning and execution of the enterprise AI Literacy strategy across multiple geographies and business functions.
• Develop and maintain scalable operating models, governance structures, processes, and delivery frameworks supporting AI Literacy initiatives.
• Manage the end-to-end delivery of virtual and in-person AI Literacy learning programs for approximately 15000 employees globally.
• Coordinate schedules, timelines, resources, dependencies, and implementation activities across multiple workstreams.
• Manage external vendors, agencies, and contractors responsible for training delivery and operational support.
• Monitor vendor performance, contractual obligations, service levels, and delivery outcomes.
• Manage program budgets, forecasts, resource plans, and operational expenditures.
• Drive continuous improvement initiatives focused on operational efficiency, scalability, and cost effectiveness.
• Implement processes and controls that support sustainable growth of the AI Literacy program.
• Lead continuous improvement efforts through data-driven decision making and performance analysis.

Director, R&D Data Science – Operations & Community Lead

• Be a hands-on scientific and technical leader, leading a portfolio of RWE projects, developing best practices, and mentoring team members.
• Identify common technical requirements for RWE projects, develop and maintain a common suite of tools that enable RWE data scientists to accelerate project delivery.
• End-to-end expertise in RWE studies including conceptualizing research questions, data feasibility, study design, analysis, programming, and interpretation.
• Provide thought leadership and hands-on programming expertise for developing and applying Real-World Data (“RWD”) methodologies to mitigate observed and unobserved biases in the execution of external control arm studies, hybrid control studies, comparative effectiveness analyses, etc.
• Provide thought leadership and hands-on programming expertise to generate actionable insights from post-hoc RCT analyses, observational databases, and literature reviews to support regulatory agency interactions.
• Independently create study protocols, statistical analysis plans, and statistical programming deliverables including analysis-ready data, tables and figures.
• Partner with the Data Science Therapeutic Area scientists to conceptualize, lead, shape and deliver Real World Evidence.

• Define and execute TKO’s enterprise-wide data strategy, architecture, governance, and data products
• Own and evolve TKO’s enterprise data warehouse — cloud infrastructure, ingestion pipelines, and integrations
• Ensure platform reliability at TKO’s operating cadence
• Define and operate TKO’s enterprise data governance framework
• Prepare data for monetization and AI consumption
• Build TKO’s internal data product capability
• Attract, develop, and retain world-class data talent; manage the Enterprise Data budget

SVP, Head of Enterprise Data

• Lead complex initiatives related to business analysis, including those that are cross functional, with broad impact, and act as key participant in data aggregation, monitoring, and reporting of stress testing and monthly loss forecast for Risk Analytics.
• Collaborate with stakeholders and business partners to identify requirements, drive process and technology improvements, and ensure compliance with Finance and Risk governance frameworks, controls, and documentation requirements
• Support end-to-end implementation activities, including test planning and execution, documentation updates, stakeholder support, issue resolution, and post-implementation operational readiness.
• Review and analyze data to provide results specific to businesses supported.
• Make decisions in complex product strategies and risk exposure, requiring solid understanding of business unit projects and regulatory responses, policies, procedures, and compliance requirements that influence and lead Analytic and Reporting to meet deliverables and drive new initiatives.
• Collaborate and consult with peers, less experienced to more experienced managers, to resolve production, project, and regulatory issues, and achieve risk analytics goals.
• Lead projects, teams, and mentor.

Lead Risk Analytics Consultant – Corporate Credit Risk Oversight, Allowance

• Lead a data science team and cross-functional projects
• Innovate and improve machine learning models
• Partner with business leaders and technical experts across the company
• Develop new data sources and improve our modeling methodology
• Apply models with sound risk management

Director of Data Science, Credit Risk

• Manage multiple projects on a campus(es) and maintain updated budgets, schedules, and status reports for each
• Create and communicate updates on development program & project status on a monthly basis suitable for executive level reviews.
• Effectively present information in a manner to support efficient decision making
• Work with QTS stakeholders, design, and construction teams to create a master development program for site(s), including a complete campus design solution and capital budget.
• Manage entitlement and permitting needs for each assigned site project(s)
• Implement and manage multi-phased site development plans to achieve time, budget, and quality standards in a predictable fashion.
• Continuously update a campus master plan to provide predictable statistics in a dynamic environment
• Write scopes of work for design, construction, commissioning services & participate in procurement and project cost estimates
• Evaluate and level pricing proposals for design, construction, and commissioning services
• Work closely with strategic procurement team on equipment procurement and delivery process
• Ensure appropriate submittals are coordinated with site stakeholders
• Monitor & create project budget / cost-to-date against overall project budget.
• Establish project schedules and manage teams to on-time completion
• Review and approve monthly pay applications from the contractors
• Review change order requests from contractors and negotiate pricing
• Establish site construction security procedures in conjunction with site security team
• Develop plans for product deployment and review / communicate plans with QTS staff involved
• Collaborate with Sales Engineers and Product teams to aid in custom deal solutioning for prospective clients within the applicable schedule and budget for an assigned location.
• Establish and maintain relationships serving as liaison with key QTS stakeholders
• Represent QTS Interests as leader in OAC meetings
• Create & build relationships that enhance QTS’s ability to be a leader in creating the World’s Most Valuable Data Center Real Estate
• Aid in due diligence efforts for potential new sites on an as-needed basis
• Work with the internal development team to enhance project management processes and protocols

Data Center Construction Project Manager

• Manage multiple projects on a campus(es) and maintain updated budgets, schedules, and status reports for each
• Create and communicate updates on development program & project status on a monthly basis suitable for executive level reviews
• Effectively present information in a manner to support efficient decision making
• Work with QTS stakeholders, design, and construction teams to create a master development program for site(s), including a complete campus design solution and capital budget
• Manage entitlement and permitting needs for each assigned site project(s)
• Implement and manage multi-phased site development plans to achieve time, budget, and quality standards in a predictable fashion
• Continuously update a campus master plan to provide predictable statistics in a dynamic environment
• Write scopes of work for design, construction, commissioning services & participate in procurement and project cost estimates
• Evaluate and level pricing proposals for design, construction, and commissioning services
• Work closely with strategic procurement team on equipment procurement and delivery process
• Ensure appropriate submittals are coordinated with site stakeholders
• Monitor & create project budget / cost-to-date against overall project budget
• Establish project schedules and manage teams to on-time completion
• Review and approve monthly pay applications from the contractors
• Review change order requests from contractors and negotiate pricing
• Establish site construction security procedures in conjunction with site security team
• Develop plans for product deployment and review / communicate plans with QTS staff involved
• Collaborate with Sales Engineers and Product teams to aid in custom deal solutioning for prospective clients within the applicable schedule and budget for an assigned location
• Establish and maintain relationships serving as liaison with key QTS stakeholders
• Represent QTS Interests as leader in OAC meetings
• Create & build relationships that enhance QTS’s ability to be a leader in creating the World’s Most Valuable Data Center Real Estate
• Aid in due diligence efforts for potential new sites on an as-needed basis
• Work with the internal development team to enhance project management processes and protocols

Development Project Manager – TFO Data Center Construction

• Manage multiple projects on a campus(es) and maintain updated budgets, schedules, and status reports for each
• Create and communicate updates on development program & project status on a monthly basis suitable for executive level reviews.
• Effectively present information in a manner to support efficient decision making
• Work with QTS stakeholders, design, and construction teams to create a master development program for site(s), including a complete campus design solution and capital budget.
• Manage entitlement and permitting needs for each assigned site project(s)
• Implement and manage multi-phased site development plans to achieve time, budget, and quality standards in a predictable fashion.
• Continuously update a campus master plan to provide predictable statistics in a dynamic environment
• Write scopes of work for design, construction, commissioning services & participate in procurement and project cost estimates
• Evaluate and level pricing proposals for design, construction, and commissioning services
• Work closely with strategic procurement team on equipment procurement and delivery process
• Ensure appropriate submittals are coordinated with site stakeholders
• Monitor & create project budget/cost-to-date against overall project budget.
• Establish project schedules and manage teams to on-time completion
• Review and approve monthly pay applications from the contractors
• Review change order requests from contractors and negotiate pricing
• Establish site construction security procedures in conjunction with site security team
• Develop plans for product deployment and review/communicate plans with QTS staff involved
• Collaborate with Sales Engineers and Product teams to aid in custom deal solutioning for prospective clients within the applicable schedule and budget for an assigned location.
• Establish and maintain relationships serving as liaison with key QTS stakeholders
• Represent QTS interests as leader in OAC meetings
• Create & build relationships that enhance QTS's ability to be a leader in creating the World's Most Valuable Data Center Real Estate
• Aid in due diligence efforts for potential new sites on an as-needed basis
• Work with the internal development team to enhance project management processes and protocols

Data Center Construction Regional/Program Manager

• Analyze, estimate & define data transformation req. to load data into EDW, Snowflake, Postgres, S3 (enterprise production & custom-built analytics environment).
• Create ETL architecture & design flows to illustrate data mvmt from production to analytics environments (new & legacy AWS analytics environments).
• Design & develop database code software.
• Analyze project & make strategy for analytics data solutions & AI model support & deployment.
• ETL & analytics S3 storage projects.
• Lead analytics/data science ETL projects.
• Lead team.
• Evaluate organization's tech. needs, create POCs for new implementation or tech. enhancement & recommend improvements.

Director, Data Science Operations

• Trusted customer master (the customer lighthouse): a single, governed customer master that includes IDN → member facility → service-line hierarchy, with GPO affiliation (primary and aggregation group), and identifiers integrated with market data
• Fixed, codified metric methodology that serves as one trusted source of truth: a documented, defensible calculation methodology for share-of-wallet, penetration, and addressable/potential value (built on market and GPO data)
• Redefined KPI framework: a smaller, value-based set of leading indicators that measurably changes where RVPs and reps spend their time and holds them accountable to execution
• Initiative tracking linked to EBITDA: a live tracking model where every transformation initiative is linked to its EBITDA impact (calculation owned by Finance) and rolls up to the North Star
• Phase 2 Lighthouse Expansion to the Product Lighthouse: a single, product master data methodology stood up on the same governed model
• Owns: Customer master data methodology and governance: hierarchy logic, GPO affiliation, identity-resolution rules, identifier crosswalks, and integration of market data into the customer lighthouse
• Calculation, methodology, and source of truth for derived commercial metrics (share-of-wallet, penetration, potential/addressable value)
• Design of Commercial KPIs including what is measured, how it is defined, and how it drives focus and accountability
• Initiative tracking model: tracking commercial transformation initiatives and linking each to its EBITDA impact
• The Definitive Healthcare (market-data) relationship, including managing scope changes within an approved budget
• Recommends: Where RVPs and reps should focus from data-driven insights to surface highest value whitespace and penetration opportunities from the trusted data for sales leadership and CVM to act on
• Data, pipeline, and tooling requirements to the ops-data organization focusing on the upstream demand that governs their build
• Sequencing of the lighthouse roadmap (customer → product) and the associated stewardship-ownership decisions
• Informs: Regional and rep-level performance transparency through the redefined KPI set
• Cross-functional and Finance leadership on data-quality gaps, unowned stewardship, and methodology changes that affect reported numbers

Commercial Analytics Lead

• Implements complex projects for institutional retirement plans with high quality data outcomes
• Advises on data solutions regarding complex plan administration challenges
• Resolves risks and issues for complex retirement plan implementations in a timely manner
• Engages and leads appropriate resources in a highly-matrixed environment to resolve data issues
• Guides less experienced team members regarding retirement plan transition challenges that require more advanced knowledge
• Ensures internal tools and procedures are updated based on new learnings

Transitions Data Lead II

• Own the vision, roadmap, and lifecycle of data products
• Partner with IT leaders, analytics teams, and data engineers to translate business needs into clear product requirements and prioritized backlogs
• Drive standardization of key metrics and definitions to enable consistent, decision‑ready insights across IT
• Ensure data products meet enterprise standards for quality, security, governance, and auditability
• Lead cross‑functional delivery from discovery through production, including release planning and ongoing optimization
• Measure and drive adoption, usage, and value realization of data products
• Communicate product strategy, progress, and insights to IT executive stakeholders and senior management
• Continuously improve data product ways of working, leveraging agile and product management best practices

Data Scientist jobs in United States

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Chemical Data Scientist

Principal Health Data Scientist

AI & Data Science – LLMs, Healthcare Insights

Data Programs Manager

Lead Data Scientist

Data Scientist – Predictive Maintenance

Senior Principal Scientist, Data Science RWE

Director, R&D Data Science – Operations & Community Lead

Senior Principal Scientist, Data Science RWE

Director, R&D Data Science – Operations & Community Lead

SVP, Head of Enterprise Data

Lead Risk Analytics Consultant – Corporate Credit Risk Oversight, Allowance

Director of Data Science, Credit Risk

Data Center Construction Project Manager

Development Project Manager – TFO Data Center Construction

Data Center Construction Regional/Program Manager

Director, Data Science Operations

Commercial Analytics Lead

Transitions Data Lead II

Senior Data Product Manager