Pager Health logo
Pager Health

Powering connected healthcare

Senior Data Scientist

Data ScientistData ScientistFull TimeRemoteSeniorTeam 201-500Since 2014H1B No SponsorCompany SiteLinkedIn

Location

Colorado + 3 moreAll locations: Colorado | Nevada | New York | Washington

Posted

23 hours ago

Salary

$140K - $150K / year

Seniority

Senior

Bachelor Degree7 yrs expEnglishPythonSQL

Job Description

Senior Data Scientist

Pager Health

• Lead the design, development, deployment, and optimization of machine learning, predictive analytics, and AI-powered solutions. • Translate business challenges and opportunities into analytical approaches, model specifications, and measurable success criteria. • Apply advanced statistical analysis, machine learning techniques, and data science methodologies to solve complex business problems. • Analyze large, complex datasets to identify trends, patterns, opportunities, and actionable insights. • Develop and maintain model documentation, technical specifications, and implementation plans. • Stay current with emerging technologies, tools, and best practices in data science, machine learning, and artificial intelligence. • Design and execute comprehensive validation and evaluation strategies for machine learning and generative AI solutions. • Develop benchmarking frameworks and success metrics to assess model performance, reliability, and business impact. • Evaluate model quality using quantitative and qualitative measures, including accuracy, precision, recall, robustness, latency, and business outcome metrics. • Assess generative AI applications for response quality, grounding, relevance, consistency, and hallucination risk. • Identify and mitigate risks related to bias, fairness, explainability, privacy, and model reliability. • Perform model validation, testing, and performance assessments prior to production deployment. • Establish monitoring processes and evaluation methodologies to ensure continued model effectiveness and alignment with business objectives. • Design, execute, and analyze experiments, including A/B tests and statistical studies, to measure product and business outcomes. • Define key performance indicators and success metrics for machine learning and AI initiatives. • Measure and communicate the impact of analytical solutions through statistical analysis and quantitative methods. • Partner with stakeholders to define hypotheses, success criteria, and decision-making frameworks. • Use experimentation and data-driven insights to guide product, operational, and strategic decisions. • Collaborate with Engineering and Data Engineering teams to implement, operationalize, and scale models in production environments. • Monitor deployed models for performance degradation, model drift, data quality issues, and changing business conditions. • Recommend retraining, optimization, or replacement strategies based on model performance and evolving business needs. • Support the creation of scalable, maintainable, and reliable AI and machine learning solutions. • Ensure model deployment processes align with engineering best practices and operational requirements. • Partner with Product, Engineering, Analytics, and business stakeholders to prioritize opportunities and deliver high-impact solutions. • Communicate complex analytical findings and technical concepts to both technical and non-technical audiences. • Present recommendations, insights, and model performance results to leadership and project teams. • Support technical reviews, project planning, and delivery activities across cross-functional initiatives. • Contribute to knowledge sharing, documentation, and best practices within the data science organization. • Provide technical guidance and mentorship to junior team members and peers as needed.

Job Requirements

  • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field; Master's degree preferred.
  • 7+ years of experience in data science, machine learning, advanced analytics, or a related field.
  • Demonstrated experience developing and deploying machine learning models in production environments.
  • Strong foundation in statistics, hypothesis testing, experimental design, and predictive modeling.
  • Experience working with large datasets and distributed data processing environments.
  • Proficiency in Python, SQL, and common data science and machine learning frameworks.
  • Experience communicating analytical findings and recommendations to business and technical stakeholders.
  • Proven ability to lead projects and collaborate effectively across cross-functional teams.

Benefits

  • stock options
  • range of medical benefits
  • dental benefits
  • vision benefits
  • financial benefits
  • generous PTO
  • stipends for professional development
  • wellness benefits

Related Categories

Related Job Pages

More Data Scientist Jobs

Celerion logo

Clinical Data Manager – External Site Studies

Celerion

Celerion Can Take You from First-In-Human through Proof-of-Concept.

Data Scientist23 hours ago
Full TimeRemoteTeam 1,001-5,000Since 1971H1B Sponsor

• Deliver comprehensive data management services across all study phases • Independently own assigned data management studies and deliverables from startup through database lock, proactively identifying risks, resolving issues, communicating status, and escalating when appropriate • Ensure clinical databases are complete, accurate, and compliant with Sponsor and regulatory standards • Serve as primary Sponsor contact for data management activities • Lead data management communications and coordinate with internal and external teams to ensure timely delivery of study milestones and progress updates • Train site staff (CRCs, CRAs, PIs) and client teams on EDC systems • Oversee CRF lifecycle from design to final delivery • Conduct User Acceptance Testing (UAT) and ensure database setup aligns with specifications • Develop and manage essential study documents (e.g., Data Management Plan, CRF Completion Guidelines, Validation Plans, SAE Reconciliation Plans) • Review and clean clinical data, manage queries, and reconcile third-party data • Coordinate database lock and final data delivery • Identify risks and proactively resolve project issues • Provide exceptional service to internal and external stakeholders

United States
Wealthsimple logo

Senior Data Scientist, Crypto

Wealthsimple

All of your investing, made simple.

Data Scientist23 hours ago
Full TimeRemoteTeam 1,001-5,000Since 2014H1B No Sponsor

• Partner with Product, Engineering, Design, and Operations to inform and shape product strategy, prioritization, and decision-making • Develop metrics, data models, and analytical frameworks that improve how teams understand customer behaviour and business performance • Identify opportunities to improve customer experience, growth, retention, and operational efficiency through data • Translate complex business questions into clear recommendations and actionable insights • Proactively surface trends, risks, and opportunities that help the team focus on the highest-impact work • Collaborate with Analytics Engineering to improve the quality, scalability, and usability of data foundations for the team

Canada
CA$151K - CA$189K / year
Terray Therapeutics logo

Scientist, In Vivo Pharmacology

Terray Therapeutics

Chemistry is the key to drug discovery, but chemical data is stuck in the twentieth century. We’re generating precise chemical datasets purpose-built to propel drug discovery into the information age — and we’re doing it on a larger scale and faster than has ever before been possible. Terray Therapeutics is a biotechnology company led by pioneers and long-time leaders in artificial intelligence, synthetic (medicinal) chemistry, biology and preclinical development, automation, and nanotechnology. Chemical datasets generated using our novel ultra-dense microarray technology work seamlessly with our integrated machine learning and computational platform to systematically map biochemical interactions between small molecules and causes of disease. Iterative cycles of virtual molecular design and experimentation power AI and machine learning models, which in turn guide the next cycle of design. With a chemistry engine that measures billions of interactions daily and becomes increasingly precise with every cycle, we can answer an unprecedented array of questions — deriving insights that enable us to predictably create drugs for patients in need.

Full TimeRemoteTeam 58Since 2018

Role Description Terray Therapeutics is seeking a highly motivated and experienced in vivo scientist with expertise in models of autoimmunity and inflammation to join our Translational Biology team. In this role, the candidate will serve as a scientific and operational lead for outsourced in vivo pharmacology and nonclinical safety/toxicology studies, with responsibilities including study design, execution and monitoring, vendor oversight, project management and cross-functional coordination. The position will report to the Director of Translational Biology. - Provide scientific leadership and oversight for in vivo pharmacology studies focused on inflammation, autoimmunity, or related therapeutic areas in support of advancing our pipeline programs. - As the pharmacology representative, collaborate cross-functionally with preclinical teams, project leads, and external consultants to advance our pipeline programs through in vivo studies. - Lead and monitor outsourced in vivo pharmacology and nonclinical safety/toxicity studies conducted at CROs, ensuring scientific rigor, protocol compliance, data quality, and timely execution. - Contribute to study design, protocol development and review, endpoint selection and data interpretation. - Review study reports, datasets and summaries to ensure scientific accuracy and completeness. - Coordinate study timelines, logistics, milestones, budgets and deliverables across multiple external vendors and internal stakeholders. - Manage CRO relationships, including vendor selection, performance oversight, issue resolution and communication. - Maintain study documentation, ensuring compliance with regulatory requirements and company policies. - Present study updates and recommendations to project teams and leads. - Support contract management activities (scopes of work, purchase orders, invoice tracking). Qualifications - Ph.D. degree in biology, immunology, pharmacology, toxicology, or a related field. - 3+ years of experience in biotech or pharmaceutical industry supporting nonclinical drug development programs. - Strong scientific background in inflammation, immunology, or immune-related diseases. - Extensive experience with rodent in vivo pharmacology and translational disease models. - Strong scientific data analysis, interpretation, and problem-solving skills. - Strong understanding of nonclinical drug development workflow. - Experience managing or monitoring outsourced studies at CROs. - Demonstrated project management and organizational skills with the ability to manage multiple studies and priorities simultaneously. - Excellent written, verbal, and presentation skills. - Ability to work effectively in cross-functional teams and to thrive in a highly collaborative research environment. Requirements - Experience with vendor oversight, contract management, and budget tracking. - Experience supporting IND-enabling and preclinical development programs. - Knowledge of GLP and non-GLP study conduct and non-clinical assessment. - Familiarity with IACUC regulations and animal welfare standards. Benefits - Compensation: $120,000 – $175,000 annually, depending on experience. - Participation in the Company’s stock option plan. - 3% retirement safe harbor contribution. - Fully paid health, dental, vision insurance for employees, spouses, partners, and families. - Above-market life insurance and disability coverage. - Additional benefits to explore during the offer process.

United States
$120K - $175K / year
HealthCare.com logo

Senior Applied AI Data Scientist

HealthCare.com

Work with us! Now hiring across the globe.

Full TimeRemoteTeam 201-500Since 2014H1B Sponsor

• Build AI-assisted workflows and internal tooling • Prototype and productionize LLM-enabled applications • Develop scalable analytics and decision-support systems • Improve self-service data access safely and responsibly • Reduce operational burden through automation and intelligent systems • Help evolve internal governance and semantic consistency practices

United States