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Data Science Research Assistant Remote Jobs in Florida

Milliman

Strategic Data Partnership Manager

Tampa, FL · Remote

... life sciences research, and provider performance solutions. We sit in the middle of that ... This position is fully remote, while occasional travel may be required. Primary Responsibilities:

Booz Allen Hamilton, Inc.

Data Scientist

Tampa, FL · On-site +1

$99K - $225K/yr

Remote Work: No Job Number: R0245472 Location: Tampa,FL,US Share job via: Share Data Scientist The ... As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with ...

micro1 AI

Digital Chemistry Specialist - Remote

Tampa, FL · Remote

$90 - $120/hr

Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science. * Experience collaborating in multidisciplinary or remote project environments is ...

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Data Science Research Assistant Remote information

What are the key skills and qualifications needed to thrive as a data science research assistant remote?

To thrive as a Data Science Research Assistant (Remote), a solid background in statistics, programming (Python or R), and data analysis, often supported by relevant coursework or a degree, is essential. Familiarity with data visualization tools (e.g., Tableau), databases (SQL), and platforms like Jupyter Notebook, as well as experience with machine learning libraries, is typically required. Strong problem-solving abilities, attention to detail, self-motivation, and effective remote communication skills make candidates stand out. These competencies are crucial for managing complex data tasks, collaborating with team members virtually, and delivering reliable analytical insights.

What are common challenges faced by remote data science research assistants, and how can they be addressed?

Remote Data Science Research Assistants often encounter challenges such as maintaining clear communication with team members, managing time across different projects, and accessing necessary datasets or computing resources. Overcoming these hurdles typically involves leveraging collaboration tools like Slack or Zoom for regular check-ins, setting clear expectations with supervisors on deliverables, and ensuring secure, remote access to data and software. Proactively seeking feedback and participating in virtual team meetings can help foster a sense of connection and keep projects on track.

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

AspectData Science Research Assistant RemoteData Analyst Remote
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldBachelor's or Master's in Data Analysis, Statistics, or related field
Work EnvironmentRemote research projects, academic or research institutionsRemote data interpretation and reporting for various industries
Employer & Industry UsageUniversities, research labs, tech companiesBusiness, finance, healthcare, marketing

While both roles involve working with data remotely, Data Science Research Assistants focus on research projects, often in academic or research settings, requiring a strong foundation in data science and statistics. Data Analysts typically analyze and interpret data for business insights across various industries. The roles share similar credentials but differ in their primary focus and work environment.

What is a data science research assistant remote?

A Data Science Research Assistant (Remote) is a professional who supports data scientists and research teams by collecting, cleaning, analyzing, and visualizing data, often from a remote location. Their responsibilities may include assisting with experiment design, performing statistical analyses, preparing datasets, creating reports, and helping to develop or test machine learning models. Working remotely, they utilize collaboration tools and cloud platforms to work efficiently with distributed teams. This role is ideal for individuals with strong analytical skills, programming knowledge (such as Python or R), and an interest in research and data-driven problem solving.
What are popular job titles related to Data Science Research Assistant Remote jobs in Florida? For Data Science Research Assistant Remote jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Data Science Research Assistant Remote jobs in Florida look for? The top searched job categories for Data Science Research Assistant Remote jobs in Florida are:
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Data Science Research Assistant Remote jobs near you

Senior Product Manager, Life Sciences Data Products

Beacon Talent

Miami, FL • On-site, Remote

$152K - $158K/yr

Full-time

Re-posted 7 days ago

Job description

Senior Product Manager, Life Sciences Data Products (Applied AI)

Location: U.S. (Remote-first) with optional hub-based hybrid
Employment: Full-time
Level: Senior IC (high ownership)
Start: ASAP / Flexible

Beacon Talent is leading a confidential search for a venture-backed company building an applied AI + data platform that supports life sciences teams (biopharma, medtech, and research organizations) with secure access to real-world clinical datasets and tooling that accelerates discovery and development while maintaining high standards for privacy, quality, and responsible use.

The Role

As Senior Product Manager, Life Sciences Data Products, you will own the strategy and execution for a portfolio of data-driven products used by life sciences customers to find, access, evaluate, and operationalize complex clinical datasets for R&D and clinical development workflows.

This is a hands-on, high-agency role—ideal for a PM who loves ambiguous problem spaces, can translate market signals into crisp product bets, and can partner deeply with engineering and data teams to ship scalable product capabilities.

What You’ll Own

  • Product vision & roadmap: Define the life sciences product strategy, identify the highest-leverage problems, and translate them into a sequenced roadmap with measurable outcomes.

  • Discovery & validation: Run customer interviews, workflow mapping, and opportunity sizing to determine what to build, what to standardize, and what to avoid as one-off services.

  • Scalable data products: Build repeatable “productized” capabilities that improve dataset usability, governance, search/retrieval, cohort building, and downstream analytics readiness.

  • AI-assisted workflows: Partner with technical teams to design automation that reduces friction in data access and analysis (e.g., metadata enrichment, quality signals, dataset packaging, evaluation tooling).

  • Execution leadership: Write requirements, define success metrics, manage tradeoffs, and drive delivery from concept through launch—iterating based on usage and customer outcomes.

  • Cross-functional alignment: Collaborate closely with go-to-market partners to ensure positioning, packaging, and feedback loops inform the roadmap without turning the product into custom projects.

  • Market awareness: Stay current on life sciences R&D and clinical development trends and incorporate them into differentiation and product choices.

What We’re Looking For

Required

  • 5+ years building data products or platforms for life sciences and/or healthcare customers.

  • Strong product discovery muscle: customer interviews, problem framing, prioritization, and roadmap ownership.

  • Technical fluency across data infrastructure, APIs, pipelines, and working concepts in ML-enabled products (no need to code).

  • Track record partnering with engineering and data teams to deliver complex, high-impact product work.

  • Excellent communication—credible with technical teams and clear with non-technical stakeholders.

  • Comfort operating in a fast-moving environment with evolving inputs and limited process.

Nice to have

  • 0→1 product experience or taking early products to scale in a regulated domain.

  • UX/product design sensibility with strong intuition for end-user workflows.

  • Prior experience in analytics, data science, or experimentation.

  • Familiarity with privacy, governance, and quality frameworks for sensitive datasets.

Why This Role

  • Direct ownership of a high-impact roadmap at the intersection of life sciences + data platforms + applied AI

  • Meaningful influence over what becomes productized vs. service-heavy

  • Close collaboration with technical leadership and high visibility across the company

Compensation

Competitive base + equity + benefits. (Exact range varies by level and location and will be shared during the process.)