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Remote Data Science Jobs in Bolingbrook, IL (NOW HIRING)

Responsibilities may include remote data analysis, desktop engineering review, savings calculations ... Building Science, or a related technical field. * At least 2 years of relevant experience in ...

Participate in remote assignments or attend on-site sessions when required * Follow project ... Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or ...

Responsibilities may include remote data analysis, desktop engineering review, savings calculations ... Building Science, or a related technical field. * At least 2 years of relevant experience in ...

Participate in remote assignments or attend on-site sessions when required * Follow project ... Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or ...

Remote Hours: 10-20 hours/week Duration: 1-2 months minimum, with likely extension Start: Immediate ... Scientific Data Interpretation * Evidence-Based Reasoning * Technical Documentation Qualifications

Data Privacy Analyst Job Type: Contractor Location: Remote Job Overview We are seeking experienced Data Privacy Analysts to support a data privacy and AI training project focused on protecting ...

Data Quality Engineer

Chicago, IL · Remote

$118K - $141K/yr

... Remote-OH, Remote-PA, Remote-RI, Remote-VA Details Kemper is one of the nation's leading ... Bachelor's degree in Computer Science, Information Systems, or a related field; equivalent work ...

Data Quality Engineer

Downers Grove, IL · Remote

$114K - $137K/yr

... Remote-OH, Remote-PA, Remote-RI, Remote-VA Details Kemper is one of the nation's leading ... Bachelor's degree in Computer Science, Information Systems, or a related field; equivalent work ...

Showing results 41-60

Remote Data Science information

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

What are the qualifications to get a remote data science job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

What are the key skills and qualifications needed to thrive as a remote data scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

Can I work remotely as a data scientist?

Yes, many data scientist roles are available as remote positions, especially in companies that prioritize flexible work arrangements. Remote data scientists typically need strong skills in programming, data analysis, and tools like Python or R, and may require familiarity with cloud platforms and collaboration tools. Availability depends on the employer's policies and the specific job requirements.

What are the most commonly searched types of Data Science jobs in Bolingbrook, IL?

The most popular types of Data Science jobs in Bolingbrook, IL are:

What are popular job titles related to Remote Data Science jobs in Bolingbrook, IL?

For Remote Data Science jobs in Bolingbrook, IL, the most frequently searched job titles are:

What job categories do people searching Remote Data Science jobs in Bolingbrook, IL look for?

The top searched job categories for Remote Data Science jobs in Bolingbrook, IL are:

What cities near Bolingbrook, IL are hiring for Remote Data Science jobs?

Cities near Bolingbrook, IL with the most Remote Data Science job openings:

Infographic showing various Remote Data Science job openings in Bolingbrook, IL as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, and 5% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Director, Data Engineering - OptumRx Technology - Remote

UnitedHealth Group

Schaumburg, IL • Remote

Full-time

Retirement

Posted 18 days ago


Key responsibilities

  • Define and drive the enterprise data engineering and AI platform vision.

  • Lead multiple data engineering teams responsible for data ingestion, transformation, storage, and development of data pipelines and data products.

  • Partner with Data Science and AI teams to operationalize ML and GenAI solutions, including building feature stores, embedding pipelines, and enabling model deployment and monitoring.


UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

193rd of 898 rated healthcare providers


Job description

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Director, Data Engineering & AI leads the strategy, architecture, and execution of enterprise data platforms that power analytics, machine learning, and generative AI capabilities. The role is accountable for building scalable AI-ready data foundations, governing trusted data assets, enabling responsible AI adoption, and delivering business value through modern data products while leading high-performing engineering teams and driving enterprise-wide transformation.

You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges.

Primary Responsibilities:

  • AI-Ready Data Platform Strategy
    • Define and drive the enterprise data engineering and AI platform vision
    • Establish scalable data architectures to support analytics, machine learning, GenAI, and agentic AI solutions
    • Ensure data platforms are cloud-native, secure, resilient, and cost-efficient
    • Build AI-ready data foundations including semantic layers, metadata, lineage, and knowledge graphs
  • Data Engineering Leadership
    • Lead multiple data engineering teams responsible for ingestion, transformation, storage, and consumption of enterprise data
    • Establish engineering standards, best practices, and reusable frameworks
    • Oversee development of data pipelines, data products, APIs, and real-time streaming solutions
    • Drive modernization from legacy platforms to cloud-based architectures
  • AI & Machine Learning Enablement
    • Partner with Data Science and AI teams to operationalize ML and GenAI solutions
    • Build feature stores, vector databases, embedding pipelines, and RAG architectures
    • Enable model training, deployment, monitoring, and lifecycle management
    • Define standards for AI observability, explainability, and responsible AI
  • Enterprise Data Governance
    • Establish data quality, stewardship, lineage, cataloging, and master data management processes
    • Ensure compliance with regulatory, privacy, and security requirements
    • Implement governance frameworks for AI training data and AI-generated outputs
    • Drive trusted and certified data asset programs
  • Data Product Management
    • Champion a data-as-a-product mindset
    • Define ownership, SLAs, and quality standards for enterprise data products
    • Prioritize investments based on business value and AI-readiness
    • Measure adoption, quality, and business impact of data products
  • Innovation & Emerging Technologies
    • Evaluate emerging technologies in GenAI, Agentic AI, Data Fabric, Semantic Layer, Knowledge Graphs, and Intelligent Automation
    • Lead proof-of-concepts and enterprise-scale deployment strategies
    • Drive automation of engineering operations using AI-powered tooling
    • Promote innovation culture across engineering teams
  • Business & Stakeholder Engagement
    • Partner with business, product, analytics, and technology leaders to identify AI-powered opportunities
    • Translate business objectives into scalable data and AI capabilities
    • Communicate technology strategy and value realization to executive leadership
    • Influence investment decisions and roadmap priorities
  • Financial & Operational Management
    • Own platform budgets, vendor management, and resource planning
    • Optimize cloud costs and platform utilization
    • Establish KPIs for platform reliability, performance, and productivity
    • Ensure operational excellence and adherence to SLAs
  • Talent Development
    • Recruit, mentor, and develop high-performing data engineering and AI engineering teams
    • Build organizational capabilities in cloud, analytics, MLOps, GenAI, and data governance
    • Create career growth paths and succession plans
    • Foster a culture of innovation, accountability, and continuous learning
  • Key Success Metrics
    • Data quality and reliability
    • AI adoption and business value realization
    • Platform availability and performance
    • Data product usage and customer satisfaction
    • Engineering productivity and automation
    • Cloud cost optimization
    • Regulatory and governance compliance
    • Team engagement and retention
       

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications: 

  • Undergraduate degree or equivalent experience
  • Hands-on experience with AI, creating agentic solutions
  • Solid knowledge of Unix and shell scripting
  • Solid understanding of DWH principles, Spark/Databricks, Azure Architecture 
  • Solid understanding of Data Architecture and Azure Cloud
  • Understanding of QA and testing automation process
  • Understanding and knowledge of Agile

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $134,600 - $230,800 annually based on full-time employment. We comply with all minimum wage laws as applicable.

Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.


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