This page tracks remote data scientist openings that are location-eligible for Illinois.
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• Develop and productionize machine learning models for a range of healthcare products, including monitoring controlled substance handling and patient privacy, and inventory management • Define and track KPIs to measure model performance and business impact • Collaborate with product teams and customers to scope analytics projects and build prototypes. Translate ambiguous business problems into well defined, quantitative, and testable hypotheses. • Communicate technical findings to both technical and non-technical stakeholders, including customers. Present results and recommendations in customer-facing meetings. • Inform product roadmaps, evaluate technical feasibility, and assess project risks. • Quickly ramp up on new healthcare data sources as products evolve and adapt to new ML techniques and tools as needed for product requirements • Raise the skill level of the entire analytics team by modeling strong research communication through team presentations and documentation. Drive collaboration through code reviews, experimental design feedback, and participation in model evaluation discussions.
VRChat offers an endless stream of social VR experiences by giving the power of creation to its community.
• Partner with cross-functional teams to define high-impact product questions, success metrics, and decision frameworks. • Analyze user behavior, creator activity, content ecosystems, retention, growth, monetization, and social dynamics to identify opportunities and risks. • Design and analyze experiments, including A/B tests and other causal measurement approaches, to evaluate product launches, campaigns, and strategic initiatives. • Define and improve core product metrics, dashboards, diagnostic views, and recurring reporting that help teams understand what is changing and why. • Build durable analytical assets such as reusable notebooks, data marts, metric definitions, self-serve dashboards, and analysis templates. • Use AI-assisted and agentic workflows to accelerate analysis, automate repetitive investigation, improve documentation, and build lightweight internal tools for common analytical questions. • Collaborate with Data Engineering and product teams to improve data quality, instrumentation, modeling, and source-of-truth definitions. • Communicate findings clearly to technical and non-technical audiences, including senior stakeholders, and influence product decisions through evidence and judgment.
• Research, design, and build ML models across a range of use cases • Work across the full deployment spectrum: managed cloud ML platforms and containerized solutions built in Python • Collaborate with engineers to integrate models into production environments and uphold MLOps best practices • Preprocess and analyze large datasets; think critically about data quality and what it means for model reliability • Contribute to technical discussions across the team, fostering a culture of shared learning and continuous improvement • Translate complex ML concepts clearly for both technical collaborators and non-technical client stakeholders
UnitedHealth Group is a healthcare and well-being company that’s dedicated to improving the health outcomes of millions around the world. We are comprised of
Role Description This Data Scientist role will be a part of the Decision Sciences team in Client Center of Excellence organization. The role will be responsible for interpretation of data and business requirements to develop customer centric data driven insights and AI/ML solutions. Working in collaboration with Director, Decision Sciences and other data scientists team members, this role works to: - Assist in development of advanced AI/ML systems using techniques such as deep learning, representation learning, time-series modeling, survival analysis, and probabilistic modeling to solve complex healthcare problems. - Develop Generative AI and LLM-powered solutions including retrieval-augmented generation (RAG) pipelines, domain-adapted LLMs, and AI copilots for enterprise workflows. - Work with business stakeholders to develop business solutions based on data driven insights to solve complex business problems. - Be a key contributor in projects that combine diverse customer data sets to identify trends and opportunities, develop custom machine learning models, and provide recommendations to optimize the business and address data-related problems. - Coordinate with different functional teams to improve customer data architecture, ensure accuracy of model output and implement new data gathering processes. - Create customized summaries, business presentations and documentation for internal business clients based on the results of research. - Collaborate with engineering, platform, and product teams to operationalize scalable AI/ML and GenAI systems within enterprise platforms. Qualifications - High School Diploma/GED - 2+ years of experience providing data driven solutions, reports, analytics or recommendations using SQL and/or data visualization tools like PowerBI, Tableau or equivalent. - 1+ years of experience in leveraging machine learning, artificial intelligence, or applied data science to help answer business questions. - 1+ years of experience in Python-based machine learning development using frameworks such as PyTorch, TensorFlow, or equivalent. - 1+ years of experience designing and deploying production reporting, dashboards, ML models or supporting production ETL jobs. - 1+ years of experience of developing machine learning systems leveraging regression, natural language processing algorithms, classification and clustering, time-series forecasting and predictive/prescriptive modeling. Requirements - Experience working with distributed ML systems and large-scale data platforms such as Snowflake, Spark, Databricks, or other ML systems. - Experience working on cloud platforms such as AWS, Azure, or GCP. - Experience working with healthcare datasets and standards such as claims, EHR, ICD, CPT, SNOMED, FHIR, or HL7. - Experience working on development and support of data products in a business environment. Benefits - Comprehensive benefits package. - Incentive and recognition programs. - Equity stock purchase. - 401k contribution (all benefits are subject to eligibility requirements).
Hi there! We’re Razorfish. We’ve been leading the marketing industry with our digital expertise since the start of the internet. But in 2020, we did a full reboot. What’s different? It all starts with people. Weird, wonderful, complex people - with diverse backgrounds in strategy, creative and technology. But no matter how different we are, we all have one thing in common. We believe our differences are our strength. So we push for inclusion, challenge convention and bring in new perspectives, to inspire new ideas. Because when we connect by understanding what makes people different, we can create unforgettable experiences that enrich lives. Join us at razorfish.com.
Role Description We are seeking a highly skilled and technically proficient Director of Data Science to lead and scale our data science team. This individual will be responsible for driving complex modeling efforts, designing robust data pipelines, and delivering high-impact analytical solutions that influence business strategy. This role is ideal for a hands-on leader with deep expertise in machine learning, statistics, and data infrastructure. Responsibilities - Team Leadership & Strategy - Lead and mentor a multidisciplinary team of data scientists and ML engineers. - Partner cross-functionally with engineering, product, analytics, and business stakeholders to identify opportunities for data-driven innovation within an agile environment. - Uncover deep insights from data and effectively connect them to user behaviors through compelling storytelling. - Technical Execution - Architect, deploy, and validate advanced machine learning models and algorithms for prediction, optimization, segmentation, and recommendation. - Review and guide experimentation, statistical modeling, and A/B testing across products and initiatives. - Ensure scalable deployment of ML solutions into production in collaboration with engineering teams. - Operational Excellence - Define and uphold best practices in model development, versioning, monitoring, and reproducibility. - Implement frameworks for model governance and performance tracking. - Contribute to building a modern data science stack that supports experimentation, feature engineering, and model lifecycle management. - Data Infrastructure & Collaboration - Guide the development of robust data pipelines, feature stores, and model-serving architectures. - Advocate for sound data management and partner with data engineering on upstream data quality and infrastructure needs. - Thought Leadership - Stay abreast of emerging techniques in AI/ML and evaluate applicability to our business challenges. - Cultivate a culture of curiosity, experimentation, and scientific rigor. Qualifications - 8+ years in data science or machine learning roles, with at least 3–5 years leading teams. - Degree in Computer Science, Statistics, Mathematics, or a related technical field (MS/PhD preferred, or undergraduate degree with relevant work experience). - Deep experience with Python, SQL, and modern ML libraries (e.g., scikit-learn, statsmodels, TensorFlow, PyTorch). - Proven ability to scale ML solutions in production environments (e.g., via cloud platforms like AWS/GCP). - Experience in digital product development, particularly with web or app platforms, demonstrating an ability to effectively contribute to the lifecycle of digital products. - Strong understanding of experimental design, causal inference, and statistical testing. - Exceptional communication skills with the ability to translate technical work into business impact. Benefits - Paid Family Care for parents and caregivers for 12 weeks or more. - Monetary assistance and support for Adoption, Surrogacy, and Fertility. - Monetary assistance and support for pet adoption. - Employee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance. - Tuition Assistance. - Paid time off that includes Flexible Time off, Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more. - Matching Gifts programs. - Flexible working arrangements. - ‘Work Your World’ Program encouraging employees to work from anywhere. - Publicis Groupe has an office for up to 6 weeks a year (based upon eligibility). - Business Resource Groups that support multiple affinities and alliances.
WSP USA is the U.S. operating company of WSP, one of the world's leading engineering and professional services firms. Dedicated to serving local communities. Designs lasting solutions in the buildings, transportation, energy, water, and environment markets. More than 15,000 employees in over 300 offices across the U.S.
Role Description WSP is seeking a Lead Mine Reclamation Soil Scientist to join our Mine Closure team. The preferred location is in our Albuquerque, New Mexico office; however, other WSP office locations or a remote position may be considered for the right candidate. You will lead and contribute to multiple mine reclamation soil science programs in our southwest US service area with an opportunity to contribute to international projects. You will be responsible for delivering consulting services in soil science data collection and analysis, reporting, and permitting in support of internal and external clients. The position focuses on hard-rock mine reclamation projects with opportunities in coal reclamation and habitat restoration. Your Impact - Lead the development of mine closure plans, soil cover designs, and revegetation protocols to close mine facilities working with other physical scientists and engineers. - Oversee borrow material investigations and soil inventories to identify suitable reclamation materials and determine soil characteristics. - Direct quantitative seepage, vegetation, and erosion monitoring studies to ensure compliance with state and federal permit requirements. - Navigate complex regulatory frameworks to secure approvals for mine operations and closure activities. - Manage a variety of soil science projects on reclaimed mine lands including field logistics, staffing, budgets and scheduling, data collection, and report generation. - Coordinate with unsaturated flow modelers to develop inputs for and analyze outputs from long-term cover stability and net percolation modeling efforts. - Develop study designs, quantitative monitoring plans, and implement field programs that may include test pitting, material characterization sampling and chemical analysis, test plot construction and monitoring, vadose zone sensor installations, and reclamation cover design and grading for closure planning. - Lead multidisciplinary field programs with teams up to 10 soil scientists, geologists, ecologists, engineers, and technicians. - Provide health and safety leadership in the field and in the office. - Collect and manage quantitative soil data including data quality assurance, compilation, analysis, and interpretation. - Nurture client relationships and actively pursue opportunities related to mining and mine closure. Identify, lead, and contribute to proposals and business development activities. - Work collaboratively with other senior members of the Mine Environment team on mine closure and reclamation projects and pursuits. Establish links with other environmental and engineering business units to support and enhance service delivery. - Create detailed reclamation plans and specialized technical reports for mine closure projects. - Effectively interact with clients, local and regional team professionals, and regulatory officials. - Potential for travel domestically and internationally. Candidates not located in Albuquerque can expect to travel to New Mexico and project sites regularly. - Guide and mentor junior staff. - Oversee and work with cross-functional teams in executing project work and collaborate in response to requests for proposals. - Exercise responsible and ethical decision-making regarding company funds, resources and conduct, and adhere to WSP’s Code of Conduct and related policies and procedures. - Perform additional responsibilities as required by business needs. Qualifications - Master of Science in Soil Science, Environmental Science, Range Science, Geology, or closely related field. Candidates with a Bachelor of Science having specific relevant experience in lieu of an advanced degree are also accepted. - 10 to 15 years of progressive experience in environmental consulting with a primary focus in mining and/or land restoration. - Strong practical experience in soil science, mine waste chemical/hydraulic characterization, soil cover design and laboratory/field testing (USDA, USCS). - Demonstrated experience with field protocols to describe and sample soils, laboratory testing protocols (USDA and USCS), and vadose zone and meteorological monitoring sensors. - Proven ability to manage and mentor junior staff in the field and office. - Experience navigating local, regional, and federal mining regulations. - Ability to manage complex programs involving the collection and analysis of large amounts of data. - Strong commitment to scientific integrity, QA/QC, workplace safety, and ethical conduct. - Manage multiple project assignments while maintaining flexibility to meet cost and schedule objectives. - Excellent technical communication skills, including preparation of high-quality reports; peer-reviewed publications are an asset. - Proficiency with GIS-based field data collection and data analysis/visualization tools (e.g., ArcGIS platforms, R, Python, Excel, Power BI). - Experience with unsaturated soil atmospheric modeling software (i.e., HYDRUS, SEEP/W, UNSAT-H, etc.). - Willingness to travel and perform physically demanding field work for environmental sampling including flexible work schedules as required. - Highly capable self-leadership with attention to detail, multi-tasking, and prioritization of responsibilities in a dynamic work environment. - Ability to work independently and provide guidance and leadership to junior team members, with strict adherence to QA/QC. - Proven track record of upholding workplace safety and ability to abide by WSP’s health, safety and drug/alcohol and harassment policies. - Occasional travel may be required depending on project-specific requirements. Preferred Qualifications - Master’s Degree is preferred. - Certified Professional Soil Scientist (CPSS) certification. - 24-Hour MSHA Part 48 Certification. - 40-Hour OSHA Health & Safety Training (HAZWOPER) (29 CFR 1910.120) preferred. - Basic First Aid and Adult CPR training desired.
Role Description Scaling.com is becoming a research and advising firm — and this role builds the research half of that identity. We are hiring a Ph.D.-level Research Data Scientist to own broader research analysis across our most valuable asset: a unique, constantly evolving dataset of 500+ Scalers actively applying one framework toward a 10x goal. Your mandate is to reverse-engineer the formula. By studying what our Scalers — especially our highest performers — actually do, you will identify the patterns, moves, and correlations that drive extraordinary scaling, and publish those findings on two tracks: - Monthly white papers for our Scaler community - Peer-reviewed articles in academic business journals This is a research lab of one, with room to become a research team you lead. You will work directly with our founders, Dr. Benjamin Hardy and Blake Erickson, who will guide and sharpen your research direction, and alongside our curriculum and data teams day to day. We are looking for someone who self-manages, sets their own research agenda, and treats this dataset as the obsession of their career. - Analyze our Scaler dataset — strategy call recordings, revenue data, and portal data — to identify meaningful patterns, themes, trends, and correlations. - Study our highest-performing Scalers to extract what differentiates them: the moves they make, what they cut, how their teams reconstitute, and how they raise their floor. - Publish a monthly white paper for the Scaler community on what's working right now — core themes, top-performer behaviors, and measurable outcomes from the last 30 days. - Publish in peer-reviewed academic business journals on a quarterly cadence, building a legitimate research line around the science of scaling. - Lead and guide our data capture — tell us what data we should be collecting from Scalers and strategists, and raise the quality of the dataset over time. - Use AI tools fluently (we use Avoma for call intelligence) to accelerate theme detection and analysis across hundreds of engagements. - Translate findings into digestible, compelling writing — and present them live to our Scaler community at events. - Build the foundation of a long-term research engine and intellectual property base for Scaling.com. Qualifications - A Ph.D. candidate, recent Ph.D. graduate, postdoctoral researcher, or early-career professor in business, psychology, organizational behavior, entrepreneurship, or a related quantitative field. - Strong quantitative and qualitative research capability — you can design a study, run the analysis, and defend the methodology. - Experience with (or a clear path to) peer-reviewed academic publishing in business or social science journals. - Exceptional writing across registers — rigorous enough for an academic journal, clear enough for a founder reading a white paper. - Fluent with AI-assisted research and analysis tools, and energized by a messy, living dataset rather than a clean archival one. - Genuinely obsessed with what drives business scaling — this is your research lab, not a job between jobs. - You've read The Science of Scaling, you connect with its ideas, and you can work inside our framework and language. - Self-managing and independent — you set the agenda, bring findings forward, and don't wait to be directed. Benefits - Paid Time Off – Includes vacation days, sick leave, and company holidays - Remote Work Flexibility – Work from the location of your choice (U.S.-based) with the structure, autonomy, and support to thrive
AI & Analytics for today’s business challenges.
• Design, develop, and deploy causal inference models (e.g., uplift modeling, synthetic control, double machine learning) to understand the true drivers of customer loyalty and measure the incremental impact of marketing interventions. • Build robust machine-learning-based forecasting and predictive models for customer lifetime evaluation (LTV) and customer churn. • Establish foundational data modeling frameworks for a brand-new Business Unit, transforming raw transactional data into scalable features. • Analyze complex customer behavior, purchase patterns, and engagement metrics to build strategies for direct revenue generation. • Perform large-scale data extraction, transformation, and analysis using SQL. • Partner with marketing, product, and business teams to understand loyalty requirements and translate business problems into analytical solutions. • Present model insights and recommendations to senior client stakeholders, clearly communicating the difference between correlation and causation. • Lead workshops and customer analytics strategy discussions with clients. • Implement and operationalize models in cloud environments.
Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic advantage for the United States. Our flagship product, Ark, supports Supply Chain, Science & Technology, Production, Sustainment, Logistics, and Modernization teams with AI-enabled Applications and best-in-class data to more rapidly imagine, develop, and field the capabilities we need. Today, the national security community and every branch of the military rely on Govini to enable faster and more informed Acquisition decisions. We firmly believe that past performance is the best indicator of future performance. If you thrive while building solutions to complex problems, are a self-starter, and are passionate about making an impact in global security, we’re eager to hear from you. Govini is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status or any other characteristic protected by law.
Role Description We are seeking an inquisitive Data Scientist to join our team, leveraging deep expertise in Artificial Intelligence and a keen understanding of complex Defense Acquisition challenges. Your primary focus will be to work with our proprietary and commercial datasets to find critical connections, derive actionable knowledge, and identify potential issues that help our government clients make more informed decisions. Your role will involve designing, developing, and rapidly deploying scalable AI solutions that transform these insights into mission-critical capabilities. You will have the opportunity to expand and grow data-driven research across Govini, leading new areas to apply advanced analytics to drive strategic business and national security results. As part of our team, you must be an AI expert with a strong command of data science fundamentals and a proven ability to bring data-driven solutions to life within the defense ecosystem. In order to do this job well, you must be a highly organized problem-solver and possess excellent oral and written communication skills, capable of translating complex AI concepts for both technical and non-technical audiences. You are independent, driven, and motivated to jump in and roll up your sleeves to get the job done. You lead by influence and motivation. You have a passion for great work and nothing less than your best will do. You share our intolerance of mediocrity. You’re uber-smart, challenged by figuring things out and producing simple, impactful AI solutions to complex defense problems. This role is a full-time position located out of our office in Arlington, VA, Pittsburgh, PA, or Remote. This role may require up to 50% travel. Scope of Responsibilities - Develop AI/ML/DS systems to address defense problems. - Develop new AI-based stack of technologies for particular customer needs. - Development of evaluation solutions for AI deployments. - Lead the end-to-end execution of AI projects, ensuring alignment with strategic objectives and timely delivery. - Work closely with partner teams, including AI research, data engineering, and software development, to deliver robust AI systems. - Collaborate with the AI leadership to clearly define product and applications scope, translating high-level requirements into actionable technical plans and delivering AI platforms and solutions. - Drive the development of scalable, AI-based platforms designed to support and power solutions for a diverse range of customers within the defense ecosystem. - Champion the introduction of new AI innovations. Stay current with the rapidly evolving fields of Artificial Intelligence, Large Language Models (LLMs), and agentic systems, and actively transfer this knowledge and best practices for implementation across the team. - Mentor and guide other team members, fostering a culture of technical excellence, continuous learning, and high-impact work. - Create agentic AI systems, using AI orchestrators and particular AI reasoning capabilities as tools. Qualifications - U.S. Citizenship is required. - Oversee the full lifecycle of AI projects within Govini AI ecosystem. - Understanding of coding AI (such as Claude Code) and experience how to use it to scale up AI team deliveries. - Ensure timely project delivery and strategic goal alignment. - Collaborate with cross-functional teams (AI Research, Data Engineering, Software Development). - Define robust software architecture for AI systems and project roadmaps. - Translate high-level AI system requirements into actionable technical plans. - Deliver production-ready AI solutions integrated with clients data platforms and workflows. - Drive the implementation of scalable AI/ML platforms. - Maintain deep expertise in cutting-edge AI, including LLMs and agentic systems. Train models, build systems based on AI innovations. - Champion innovation and best practices across the organization. - Mentor and coach team members. - Foster a high-performing culture of technical excellence and continuous growth. - Demonstrate strong National Security domain knowledge. Desired Skills - A strong publication record in the top conferences in one of the AI, ML NLP, decision science areas. - Deep knowledge of LLM and Agentic system evaluation, experience in building evaluation systems. - Experience in LLM posttraining or fine tuning. - Experience with MLOps practices, including deployment, monitoring, and management of large-scale models in cloud environments (e.g., GCP, AWS, Azure). - Track record of successfully transitioning AI research prototypes into robust, production-grade enterprise solutions. Benefits - We firmly believe that past performance is the best indicator of future performance. - If you thrive while building solutions to complex problems, are a self-starter, and are passionate about making an impact in global security, we’re eager to hear from you. Company Description Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic advantage for the United States. Our flagship product, Ark, supports Supply Chain, Science & Technology, Production, Sustainment, Logistics, and Modernization teams with AI-enabled Applications and best-in-class data to more rapidly imagine, develop, and field the capabilities we need. Today, the national security community and every branch of the military rely on Govini to enable faster and more informed Acquisition decisions.
• Own and evolve CX's Downstream Impact of Support (DSI) revenue calibration models, translating support interaction data into quantified revenue signals. • Design and execute causal inference frameworks and experiments to measure the incremental impact of CX programs (Concierge, Proactive Outreach, automation interventions) on customer retention and product engagement. • Build and maintain LLM-powered classification pipelines for CX contact taxonomy, customer friction detection, and issue attribution, partnering with Analytics Engineers to productionize models into CX's governed Source of Truth infrastructure. • Partner with CX Program Managers and Product teams to define segmentation models and behavioral signals that enable personalized experiences and improve business outcomes. • Maintain a high bar for statistical rigor across CX's analytics function, ensuring experimentation, causal analyses, and model outputs meet the standards required for executive reporting and regulatory defensibility.
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Python, SQL, AWS, Cloud, AI/ML, GCP
