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Remote Data Science Jobs in Springfield, TN (NOW HIRING)

Job Title GenAI Architect Duration: 6+ Months Location Nashville, TN Remote Work 100% Primary Skills Data Science Required Skills * 12 and 15 years of experience with Data Science AI ML and ...

Key Requirements: * 6+ years in ML engineering, data science, or applied AI roles (bonus for health ... The Local Infusion Way Local Infusion is a respectful, upbeat, and remote-first team united by our ...

This role can be based out of any of our US or European office locations or remote. How You'll Create * Monitor and analyze large-scale streaming and social data to identify patterns of suspicious or ...

Senior Product Analyst

Nashville, TN · On-site +1

$120K - $140K/yr

Remote - USA Reporting To: Principal Data Scientist Compensation: $120,000 - $140,000 / year Description As the Senior Product Analyst , you will own the analytics layer across our Product ...

Lead Cloud Architect

Nashville, TN · On-site +1

$62.75 - $80/hr

Provide architectural guidance and mentorship to data engineers, scientists, and business ... Limited Geography Remote - This is a remote position but located within a specific geography.

Lead Cloud Architect

Nashville, TN · On-site +1

$62.75 - $80/hr

Provide architectural guidance and mentorship to data engineers, scientists, and business ... Limited Geography Remote - This is a remote position but located within a specific geography.

Lead Cloud Architect

Nashville, TN · On-site +1

$62.75 - $80/hr

Provide architectural guidance and mentorship to data engineers, scientists, and business ... Limited Geography Remote - This is a remote position but located within a specific geography.

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Remote Data Science information

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.

Can I work remotely in data science?

Yes, data science is a field that often offers remote work opportunities. Many companies hire data scientists to work remotely, requiring skills in programming, data analysis, and tools like Python or R. Remote data science roles typically involve collaboration through online platforms and may require strong communication skills.

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.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Remote data science roles are open to candidates of various ages, and starting a career at 40 is possible with relevant skills in programming, statistics, and machine learning. Many professionals transition into data science later in life by gaining certifications and building portfolios, making age less of a barrier in this field.

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 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.

How can I make $100,000 a year working from home?

Remote data scientists can earn $100,000 or more annually by gaining advanced skills in machine learning, programming languages like Python or R, and data visualization tools. Building a strong portfolio, obtaining relevant certifications, and gaining experience in high-demand industries can help achieve this income level while working remotely.
What cities near Springfield, TN are hiring for Remote Data Science jobs? Cities near Springfield, TN with the most Remote Data Science job openings:
Infographic showing various Remote Data Science job openings in Springfield, TN as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 13% Part Time, 1% Temporary, 4% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Product Manager, Life Sciences Data Products

Beacon Talent

Nashville, TN • On-site, Remote

$152K - $158K/yr

Full-time

Re-posted 17 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.)