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VP COMPUTATIONAL HEALTH INSIGHTS

Thorne Research Inc.

Thorne Research Inc.

Posted on Tuesday, October 1, 2024

At Thorne we make products that matter - ones that make people's lives better. Each day begins with a mission to help others discover and achieve their best health. We count on our team members to challenge and push the boundaries to make that happen. At Thorne, you’ll be joining a team of more than 700 passionate individuals committed to our cause of providing superior health solutions.

POSITION SUMMARY: The VP, Computational Health Insights will work closely with the Chief Scientific Officer to develop and implement innovative AI-driven insights to provide personalized health and supplement recommendations across Thorne’s broad catalog based on health profiles and advanced biological testing data, whether ours or ingested from others. This role is critical in leveraging comprehensive blood panels, gut microbiome analyses, and other biomarkers to create sophisticated, data-driven solutions that translate complex biological information into actionable health insights and personalized supplement recommendations. This position will also support the potential creation of health programs under a Thorne Optimal Health Concierge program (or similar) as set based on company-wide goals and strategy.

FLSA STATUS: The U.S. Fair Labor Standards Act (FLSA) requires employers to classify their employees as being either exempt or non-exempt for the purpose of being paid overtime wages. The essential duties of this job are such that the employee is classified according to the FLSA as an EXEMPT employee.

RESPONSIBILITIES – Satisfactorily performing and/or achieving the following Responsibilities are essential duties of the job.

  • Algorithm Development and Oversight:
    • Lead the conceptualization, design, and development of advanced algorithms for personalized health and supplement recommendations.
    • Oversee the implementation and optimization of machine learning models and statistical analyses.
    • Ensure robustness, accuracy, and scalability of predictive models.
  • Data Integration and Management:
    • Manage the integration and analysis of multi-dimensional biological datasets, including blood tests, gut microbiome profiles, health profiles, and other data.
    • Develop and maintain data pipelines and databases to support efficient data processing and retrieval.
    • Implement data normalization, cleansing, and preprocessing techniques to ensure data quality.
  • Strategic Leadership:
    • Provide input to the CSO on strategic direction for data science initiatives in alignment with the company's mission and objectives.
    • Identify and evaluate new opportunities for data-driven personalized health solutions.
    • Stay abreast of industry trends and advancements in bioinformatics and computational biology to drive innovation.
  • Cross-Functional Collaboration:
    • Collaborate closely with R&D, Medical Affairs, Marketing, product development, and software engineering teams to translate scientific research into practical applications.
    • Communicate complex data science concepts effectively to non-technical stakeholders and executive leadership.
  • Regulatory Compliance and Data Governance:
    • Ensure all data science activities comply with relevant healthcare regulations, data privacy laws (e.g., HIPAA, GDPR), and ethical standards.
    • Work with legal and compliance teams to address regulatory concerns and implement necessary safeguards.
  • Product Development Support:
    • Contribute to the development and enhancement of personalized health products and services.
    • Provide data-driven insights to inform product features, user experience, and market differentiation.
    • Assist in the validation, testing, and iteration of new products based on data science findings.
  • Performance Monitoring and Optimization:
    • Establish key performance indicators (KPIs) for data science projects and monitor progress against objectives.
    • Implement processes for continuous model evaluation, validation, and refinement.
    • Utilize feedback mechanisms to improve algorithms and recommendations over time.
  • Thought Leadership and Industry Engagement:
    • Periodically represent the company at industry conferences, seminars, and networking events to enhance its reputation in personalized health and bioinformatics.
    • Publish research findings and case studies in reputable journals and industry publications.
    • Build strategic partnerships with academic institutions, research organizations, and industry leaders.
  • Technology Infrastructure and Tools:
    • Oversee the selection, implementation, and maintenance of data science tools, platforms, and technologies.
    • Ensure the data infrastructure is scalable, secure, and capable of supporting current and future analytical needs.
    • Collaborate with IT and engineering teams to maintain data security, system reliability, and performance.
  • Risk Management and Compliance:
    • Identify potential risks related to data handling, algorithmic predictions, and personalized recommendations.
    • Develop and implement risk mitigation strategies and contingency plans.
    • Ensure transparency, explainability, and accountability in all data science models and outputs.
  • Customer and Stakeholder Engagement:
    • Work with customer support, sales, and marketing teams to understand user needs, preferences, and feedback.
    • Incorporate customer insights into data science initiatives to enhance user experience and satisfaction.
    • Present data-driven findings and recommendations to internal and external stakeholders.
  • Internal Reporting and Communication:
    • Prepare and deliver regular updates, reports, and presentations to executive leadership on data science activities, achievements, and challenges.
    • Communicate the impact of data science initiatives on business objectives and key results.
    • Provide data-driven insights to support strategic decision-making across the organization.
  • Ethical Standards and Practices:
    • Promote ethical considerations in the use of data and development of algorithms within the team.
    • Stay informed about ethical issues related to AI, machine learning, and personalized medicine.
    • Implement best practices to prevent biases and ensure fairness in models and recommendations.
  • Regulatory Documentation and Support:
    • Support regulatory submissions by providing necessary data analyses, documentation, and evidence of compliance.
    • Ensure that all data science processes and models are thoroughly documented and audit-ready.
    • Liaise with regulatory bodies as needed to address inquiries related to data science activities.
  • Business Continuity and Scalability:
    • Develop plans to ensure continuity of data science operations during unforeseen events or disruptions.
    • Establish scalable processes and systems to accommodate growth and increased data volumes.
    • Continuously evaluate and improve operational efficiencies within the data science function.
  • Innovation and Research:
    • Encourage and facilitate research initiatives within the team to explore new methodologies and technologies.
    • Secure funding or grants for research projects when applicable.
    • Integrate successful research outcomes into practical applications and product offerings.
  • Mentorship and Knowledge Sharing:
    • Promote a culture of knowledge sharing and collaboration within the team and across departments.
    • Organize training sessions, workshops, and seminars to enhance organizational capabilities in data science.
    • Act as a mentor and role model for aspiring data scientists within the company.
  • Performance Appraisal and Feedback:
    • Conduct regular performance evaluations of team members, providing constructive feedback and setting clear objectives.
    • Recognize and reward outstanding contributions and achievements.
    • Address performance issues promptly and implement improvement plans as necessary.
    • Develop workflows from existing algorithms, or modify bioinformatics methods to analyze NGS, transcriptomics, proteomics, and metabolomics data. This includes development of novel bioinformatics methods as needed to answer biological questions to meet Onegevity objectives.
    • Demonstrate validity of methods through prototypes and benchmarking using appropriate controls.
    • Develop and implement procedures to version, review, test, and refactor source code and workflows for development and production.
    • Develop and implement machine learning methods using combinations of available tools and custom algorithms.

What You Need:

  • EXPERIENCE / COMPETENCIES / PROFICIENCIES– Satisfactorily achieving and/or meeting the following Experience, Competencies, and Proficiencies are essential duties of the job:
    • Experience and/or Education: Doctoral degree, postdoctoral training, and 3+ years of industry experience in an applicable area such as bioinformatics, systems biology, computer science or related required.
    • Computer and Technical Skill:Employee can use the equipment and software required to accomplish the responsibilities of the position.
      • Programming Languages: Proficiency in Python, R, C++, Java, SQL, or similar for data analysis and database management.
      • Bioinformatics Tools: Experience with genomic and microbiome analysis tools like BLAST, Bowtie, SAMtools, QIIME, and Mothur.
      • Machine Learning and Statistical Modeling: Expertise with frameworks such as TensorFlow, PyTorch, scikit-learn, and a strong background in statistical methods.
      • Data Analysis and Visualization: Proficiency with data manipulation libraries (Pandas, NumPy) and visualization tools (Matplotlib, Seaborn, Tableau).
      • Big Data and Cloud Computing: Familiarity with big data technologies like Apache Spark or Hadoop and cloud platforms such as AWS, Google Cloud, or Azure.
      • Software Development Practices: Proficient in Git for version control and Agile methodologies.
      • Data Security and Compliance: Familiarity with data encryption, HIPAA/GDPR compliance, and data anonymization techniques.
      • Algorithm Design and Optimization: Ability to design custom algorithms and optimize code for performance and scalability.

What We Offer:

At Thorne, we offer employees the chance to work with great people on exciting projects, with opportunity for growth. We also provide a full range of benefits for you and your eligible family members, such as:

  • Competitive compensation
  • 100% company-paid medical, dental, and vision insurance coverage
  • Company-paid short- and long-term disability insurance
  • Company- paid life insurance
  • 401k plan with employer matching contributions up to 4%
  • Gym membership reimbursement
  • Monthly allowance of Thorne supplements
  • Paid time off, volunteer time off and holiday leave
  • Training, professional development, and career growth opportunities
  • A safe and clean work environment

A little bit more about us.

We are committed to providing personalized health solutions, cutting-edge home health test technology, and superior supplements. To do that, Thorne owns every step of its business, from R&D to product delivery and customer service. Currently, we are:

  • The only company with exclusive partnerships with the Mayo Clinic and U.S. Olympic teams.
  • The #1 prescribed practitioner brand to 30 to 40-year-olds.
  • The #2 most dispensed supplement brand.
  • The fastest growing supplement company with sales on Amazon; the #1 practitioner brand; with an average ranking of 4.42 of 5 stars.

If you want to make a difference in the lives of others consider becoming part of the Thorne team.

THORNE IS AN EQUAL OPPORTUNITY EMPLOYER