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Flex Biotech Data Science Jobs in Florida (NOW HIRING)

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a ... Experience working within healthcare, diagnostics, biotechnology, laboratory services, or life ...

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a ... Experience working within healthcare, diagnostics, biotechnology, laboratory services, or life ...

Strong working knowledge of AI/ML techniques with the ability to flex between data science and applied ML roles as business needs evolve * Experience designing and executing pilot measurement ...

... Science, Applied Mathematics, Biotechnology preferred - Prior consulting or advisory firm ... data integration Travel Requirements Up to 80% Job Posting End Date The salary range for this ...

... Science, Applied Mathematics, Biotechnology preferred - Prior consulting or advisory firm ... data integration Travel Requirements Up to 80% Job Posting End Date The salary range for this ...

This role is essential in protecting patient safety, ensuring highquality clinical data, and ... Bachelor's degree required; a scientific or healthcare discipline is preferred. * 6 months -2 years ...

This role is essential in protecting patient safety, ensuring highquality clinical data, and ... Bachelor's degree required; a scientific or healthcare discipline is preferred. * 6 months -2 years ...

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Flex Biotech Data Science information

What is a Flex Biotech data scientist?

A Flex Biotech Data Scientist is a professional who applies data science and analytical techniques within the biotechnology sector, often in flexible or cross-functional roles. They analyze large sets of biological and clinical data to support research, development, and innovation in biotech companies. Flex roles may involve working on various projects, collaborating with interdisciplinary teams, and utilizing skills in programming, statistics, and biology. Their work helps drive discoveries, optimize experiments, and improve decision-making processes in the biotech industry.

How do Flex Biotech data science professionals typically collaborate with laboratory and research teams?

Flex Biotech Data Science professionals often work closely with laboratory scientists and research teams to interpret experimental data, refine data collection methods, and translate complex results into actionable insights. This collaboration involves regular meetings to discuss ongoing projects, sharing data findings, and providing statistical expertise to optimize research outcomes. Effective communication and a solid understanding of both computational and biological concepts are essential for bridging the gap between data science and laboratory work.

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

To thrive as a Flex Biotech Data Scientist, you need a strong background in biology, statistics, and data analysis, typically supported by a degree in bioinformatics, computational biology, or a related field. Expertise in programming languages (such as Python or R), experience with bioinformatics tools, and familiarity with platforms like SQL databases and machine learning frameworks are essential. Strong problem-solving skills, collaboration, and the ability to communicate complex findings to non-technical stakeholders make candidates stand out. These skills are crucial for extracting actionable insights from complex biological data, driving innovation, and supporting research and development in biotech environments.

What is the difference between Flex Biotech Data Science vs Flex Biotech Data Analysis?

AspectFlex Biotech Data ScienceFlex Biotech Data Analysis
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fields; knowledge of programming languages like Python or RBachelor's in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams in biotech or healthcare companies, often involving complex data modelingOperational settings focusing on data reporting, visualization, and supporting decision-making
Employer & Industry UsageUsed in biotech firms, pharmaceutical companies, and research institutionsCommon in biotech companies, healthcare providers, and research organizations

Flex Biotech Data Science roles focus on developing predictive models and advanced analytics, requiring programming skills and a strong statistical background. Flex Biotech Data Analysis positions emphasize interpreting data, creating reports, and supporting business decisions with less emphasis on coding. Both roles are vital in biotech but differ in technical complexity and responsibilities.

What are the most commonly searched types of Biotech Data Science jobs in Florida?

The most popular types of Biotech Data Science jobs in Florida are:

Infographic showing various Flex Biotech Data Science job openings in Florida as of June 2026, with employment types broken down into 85% Full Time, 13% Part Time, and 2% Contract. Highlights an 76% Physical, 3% Hybrid, and 21% Remote job distribution.

Data Scientist

Access Labs LLC

North Palm Beach, FL โ€ข On-site

Full-time

Posted 9 days ago


Job description

Job Summary:

Access Medical Laboratories is seeking an innovative and business-focused Data Scientist to join our Digital Transformation team. Reporting to the Digital Transformation Manager, this role will leverage artificial intelligence (AI), machine learning (ML), predictive analytics, and data science techniques to develop solutions that improve operational efficiency, customer experience, and business performance across Operations, Finance, Commercial/Marketing, and Laboratory functions.

The ideal candidate is passionate about transforming complex business problems into scalable AI-driven solutions and enjoys partnering with cross-functional stakeholders to identify opportunities, build predictive models, deploy solutions, and measure business impact.

Job Responsibilities:

  • Develop and implement AI and machine learning solutions that improve operational efficiency and business outcomes across multiple departments.
  • Collaborate with business leaders to identify opportunities where AI and advanced analytics can solve operational challenges.
  • Translate business needs into predictive models, machine learning algorithms, and actionable insights.
  • Design, develop, validate, and deploy production-ready AI/ML models.
  • Monitor model performance and continuously optimize solutions based on business outcomes.
  • Analyze large, complex datasets to identify trends, patterns, and opportunities for improvement.
  • Build dashboards and reporting tools that communicate insights to technical and non-technical stakeholders.
  • Partner with IT, software development, laboratory operations, finance, and commercial teams to integrate AI solutions into existing workflows.
  • Ensure data quality, governance, and compliance with healthcare data standards and organizational policies.
  • Stay current on emerging AI technologies and recommend innovative applications that drive competitive advantage.

Initial Strategic Projects

  • Develop predictive churn models to identify clients at risk and recommend retention strategies.
  • Build real-time courier delivery analytics to monitor specimen collections, deliveries, and sample stability throughout transportation.
  • Develop a "Next Best Action" recommendation engine for the Account Management team to improve customer engagement and retention.
  • Create predictive inventory and labor planning models to optimize staffing levels, inventory management, and operational efficiency.

Qualifications & Skills:

  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
  • Master's degree preferred.
  • 1-3 years of professional experience in Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics.
  • Experience developing and deploying machine learning models in a production environment.
  • Strong proficiency in Python and SQL.
  • Experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or similar frameworks.
  • Experience working with cloud platforms such as Azure, AWS, or Google Cloud.
  • Experience creating dashboards using Power BI, Tableau, or similar visualization tools.
  • Strong understanding of statistical modeling, predictive analytics, and optimization techniques.
  • Experience working within healthcare, diagnostics, biotechnology, laboratory services, or life sciences.
  • Experience with MLOps, model deployment, and automation.
  • Familiarity with Generative AI, Large Language Models (LLMs), and AI copilots.
  • Experience integrating AI solutions into enterprise applications.
  • Strong analytical and problem-solving skills.
  • Excellent communication skills with the ability to explain technical concepts to business stakeholders.
  • Ability to manage multiple projects in a fast-paced environment.
  • Collaborative mindset with strong relationship-building skills.
  • Results-oriented with a passion for innovation and continuous improvement.
  • Ability to work independently while driving cross-functional initiatives.
  • Strong project management and organizational skills.