Data Scientist

• Coach, mentor, and manage a world-class team of Partner Development Managers
• Own and execute a forward-thinking partner strategy focused on innovative ISVs and Data Providers
• Build deep relationships with Snowflake’s sales teams and drive joint sales initiatives
• Collaborate cross-functionally with Product, Industry GTM, Marketing, Operations, and Sales teams
• Track team performance, partner success metrics, and customer impact

Manager, Data Cloud Partners – Manufacturing

• 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

• Lead specific compensation data products and manage their performance and development
• Set and communicate product strategy aligned with business goals and client needs
• Improve existing products and help develop and launch new offerings
• Analyze survey results and turn findings into clear insights and client-facing stories
• Recommend product changes, priorities, and pricing to leadership
• Work with internal teams and clients to deliver effective, high-quality solutions on time

Compensation Data Product Manager

• Possess knowledge of business concepts, tools, and processes that are needed for making sound decisions in the context of the company's business; ability to apply this knowledge appropriately to various situations.
• Oversee the acquisition and consumption of data from structured and unstructured sources, while ensuring quality and comprehensiveness of data for use in analyzing business activities, detecting patterns, and communicating trends.
• Demonstrate an ability to utilize various methods and techniques, including AI, to frame opportunities and conduct analyses that result in productive decisions.
• Develop predictive data models, quantitative analyses, and implement semantic data capabilities utilizing machine learning techniques.
• Lead data exploration and analytics projects and provide on-going coaching regarding visualizations, data mining, and analytic techniques.
• Demonstrate an ability to tell a story with data and create compelling ways to use data to drive actions.

Workforce Insights Specialist – Data Science

• 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

• Lead and develop a team of data professionals, providing coaching, mentoring, and training to ensure high-quality project delivery and client satisfaction
• Oversee the processing and management of client pension data, including recurring data feeds and pension payroll file transmissions
• Direct data conversion activities for new client implementations and special projects, ensuring accurate data migration, validation, and integration
• Manage the delivery of annual actuarial valuation extracts, ad hoc reporting requests, data updates, and other client-specific processing needs
• Establish, maintain, and enforce data governance standards while identifying and implementing process improvements and system enhancements

Retirement Administration Data Manager – Defined Benefit

• Analyze product usage, deal, financial, and billing data to model pricing, packaging, and monetization scenarios.
• Design frameworks to assess willingness to pay, customer value, and price realization across customer segments and product lines.
• Conduct research on pricing strategies, packaging models, and monetization approaches across comparable and adjacent markets.
• Lead pricing and packaging strategy for new product launches, partnering with Product, GTM, and Finance to define commercial models
• Build value-based pricing and econometric models to quantify elasticity, customer ROI, and lifetime value.
• Design and execute pricing experiments
• Synthesize quantitative analysis, customer research, and competitive intelligence into executive recommendations that influence pricing strategy.
• Drive customer and prospect research to understand purchasing behavior, value perception, and pricing friction.
• Partner closely with Product, Analytics, Finance, Sales, Marketing, and Legal to deliver end-to-end pricing initiatives.
• Define KPIs and dashboards that measure pricing performance and identify optimization opportunities.
• Continuously evolve our pricing and packaging strategy to improve ARR growth, customer adoption, and value realization.

Senior Pricing Data Scientist

• 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 Internship

Data Science Intern

• Develop and implement techniques or analytics applications to transform raw data into meaningful information
• Build and evaluate Marketing ML models using First & Third Party Customer Data
• Create and manage end-to-end projects including analysis design, execution and summarization of results
• Develop scalable data pipelines for feature extraction using various cloud services
• Identify, clean, analyze and summarize data
• Prototype and implement advance solutions to enhance existing ML model performance
• Create clear documentation of research plans, results, and conclusions
• Present research and recommendations based on research findings to audiences of varying level of experience
• Collaborate with data engineering and operations teams
• Automate processes for recurring analyses or other model building activities
• Participate in planning, roadmap, and architecture discussions to help evolve AI processes

• 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

• Work as part of a team to build predictive models and applied LLMs designed to support the Kemper claims operation in areas such as fraud detection, subrogation identification, vehicle damage severity, adjuster triage and claims quality management.
• Develop and automate predictive modeling processes that can be deployed through the organization to solve reoccurring analytics needs.
• Contribute to the improvement of internal modeling capabilities and data infrastructure by suggesting and applying tweaks to existing processes.
• Monitor deployed solutions and escalate as needed.

• 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

• 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

• 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

• Responsible for end-to-end delivery of data management services
• Collaborate with internal and external customers
• Ensure staff deliver high quality, timely service and meet all regulatory requirements
• Hire, manage staff performance, utilization, retention, process improvements
• Financial management for assigned projects

Manager, Clinical Data Management

• 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.
• Support cross-functional collaboration across the QC Ecosystem and external delivery partners.
• 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.
• Contribute to phase-gate reviews and readiness assessments.
• Identify project-level risks, constraints, and issues early.
• Drive resolution through collaboration and ownership.

Project Manager – Data Center Program Delivery

• Design, build, and maintain a proprietary automation tool that streamlines the CAM deal data pipeline from intake through closing
• Own current-state data mapping across all source systems involved in deal transitions (property management platforms, CRM, financial systems, association records)
• Develop and document data transition pathways for each deal, ensuring accurate data movement between systems
• Partner with the TAAS Director to define data standards, naming conventions, and integration protocols across the deal portfolio
• Manage the Data Analyst — setting priorities and workload, reviewing data mapping output for accuracy, and providing mentorship and technical development
• Serve as the data and automation partner to both Project Managers, translating deal-level requirements into data tasks
• Maintain a master data dictionary and living system integration map while identifying and eliminating manual, repetitive data processes
• QA automation tool output and iterate rapidly based on deal learnings

Senior Data Integration & Automation Manager

• Architect and deliver enterprise AI/ML solutions
• Lead strategic initiatives and mentorship
• Collaborate with product and engineering teams

Data Scientist jobs in Illinois

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Manager, Data Cloud Partners – Manufacturing

Project Manager – Data Center Delivery

Compensation Data Product Manager

Workforce Insights Specialist – Data Science

Data Science Manager

Retirement Administration Data Manager – Defined Benefit

Senior Pricing Data Scientist

Data Science Internship

Data Science Intern

Data Scientist

Data Scientist

Data Scientist

Data Programs Manager

Data Scientist – Predictive Maintenance

Director, Data Science Operations

Commercial Analytics Lead

Manager, Clinical Data Management

Project Manager – Data Center Program Delivery

Senior Data Integration & Automation Manager

Senior Data Scientist