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Remote Amazon Data Science information

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

AspectRemote Amazon Data ScienceRemote Amazon Data Analyst
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; programming skills in Python/R; experience with machine learningBachelor's in Data Analysis, Business, or related fields; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, cross-functional projects, remote data science platformsRemote reporting, data interpretation, and visualization tasks within Amazon teams
Employer & Industry UsageAmazon's data science teams focusing on predictive modeling, ML, and AIAmazon's data analysis teams focusing on reporting, dashboards, and business insights

Remote Amazon Data Science involves developing machine learning models and advanced analytics, requiring programming and statistical skills. In contrast, Remote Amazon Data Analyst roles focus on interpreting data, creating reports, and supporting decision-making with less emphasis on coding. Both roles are integral to Amazon's data-driven strategies but differ in technical complexity and daily tasks.

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Director Data Science - Remote or Hybrid in MN or DC

UnitedHealth Group

Eden Prairie, MN • On-site, Remote

Full-time

Retirement

This job post has expired 5 days ago. Applications are no longer accepted.

UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

191st of 893 rated healthcare providers

Job description

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.
Primary Responsibilities:
  • Define enterprise data science strategy: Own and drive the technical strategy for applied machine learning, Generative AI, Agentic AI, and advanced analytics across multiple domains and healthcare use cases
  • Lead development of advanced ML, GenAI, and agentic solutions: Provide hands-on technical direction for the design, development, and deployment of machine learning, deep learning, time-series, survival analysis, large language model (LLM), and agent-based AI systems in production environments
  • Establish modeling standards and best practices: Define and standardize modeling frameworks, feature engineering approaches, prompt and context engineering practices, evaluation methodologies, and validation standards across data science teams
  • Architect scalable ML and GenAI systems: Guide the design of production-grade ML and LLM systems including data pipelines, feature stores, retrieval-augmented generation (RAG), model serving infrastructure, agent orchestration frameworks, monitoring, and retraining workflows
  • Ensure responsible and reliable AI deployment: Implement consistent practices for model interpretability, explainability, bias assessment, fairness evaluation, guardrails, human oversight, and lifecycle management across deployed predictive, generative, and agentic AI systems
  • Oversee experimentation and performance monitoring: Define experimentation, benchmarking, and monitoring strategies including drift detection, recalibration, LLM evaluation, hallucination and safety checks, tool-use reliability, and performance management
  • Provide technical leadership and mentorship: Mentor principal and senior data scientists, review technical designs and modeling decisions, and provide guidance for complex analytical, GenAI, and agentic AI challenges
  • Influence cross-functional AI delivery: Partner with engineering, data, security, product, and platform teams to align data science solutions with enterprise platforms, infrastructure, reliability requirements, AI governance expectations, and executive priorities
  • Partner with payment integrity, clinical, claims, compliance, legal, product, and operations stakeholders to translate business problems such as overpayment detection, coding validation, policy adherence, aberrant billing patterns, and prepay/postpay review into scalable AI and analytics solutions

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:
  • 12+ years of experience in data science, machine learning, or advanced analytics with 8+ years developing and deploying production ML models
  • 8+ years of experience using Python-based data science ecosystems (for example Pandas, NumPy, scikit-learn, PyTorch, or equivalent) and advanced SQL for large-scale analytics, experimentation, and data transformation
  • 7+ years of experience in senior data science or technical leadership roles influencing modeling approaches, reviewing analytical work across teams, setting standards for model development and validation, and translating complex technical tradeoffs for senior stakeholders
  • 6+ years of experience designing, deploying, or supporting production ML systems, including model serving, monitoring, retraining workflows, experimentation frameworks, ML lifecycle management, and evaluation of LLM or GenAI applications
  • 6+ years of experience working with healthcare data such as claims, EHR, pharmacy, or laboratory datasets, including familiarity with healthcare coding systems such as ICD, CPT, NDC, SNOMED, and LOINC, as well as data interoperability standards including FHIR or HL7
  • 3+ years of experience designing, building, or operationalizing Generative AI or LLM-based systems
  • 3+ years of experience applying data science, machine learning, advanced analytics, or AI techniques to healthcare program integrity, payment integrity, fraud, waste, and abuse, claims payment accuracy, improper payment reduction, coding validation, provider behavior analytics, or related healthcare financial integrity use cases
  • 1+ years of experience with Agentic AI concepts and implementations such as AI agents, agentic skills, model context protocols (MCPs), agent-to-agent (A2A) patterns, tool use, orchestration frameworks, or autonomous workflow execution
    *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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