Data Scientist and Application Developer
About The Position
We are seeking a Data Scientist and Application Developer to join a cross-functional team of engineers and scientists delivering data-driven solutions tied to manufacturing. In this role you will alternate between building business applications that enable fast, iterative analytics and operationalizing models that directly inform product quality decisions in a GMP context. You will be responsible for: Application Development (GMP + non-GMP) Build and maintain internal web applications that make analytics usable in day-to-day workflows. Develop services using Python with Flask (and/or FastAPI where appropriate), including: Lightweight APIs for data access and model execution User-facing interfaces using Flask + Jinja, with small amounts of JavaScript and optionally React for richer interactions. Implement pragmatic software engineering practices (modular design, testing, logging/monitoring hooks, clear documentation) aligned to intended use (GMP vs non-GMP). Data Science & Modeling (Manufacturing Context) Apply strong fundamentals in statistics, data extraction + cleaning, and modeling to diverse manufacturing datasets (e.g., batch/process time series, quality data, laboratory and instrument outputs). Develop, evaluate, and document models intended to support insights into manufacturing performance in a GMP environment, focusing on interpretability and lifecycle considerations. Collaborate with engineers, scientists, and quality partners to define the problem, select fit-for-purpose methods, and translate outcomes into operational decisions. Communicate findings clearly to technical and non-technical stakeholders; create reusable analysis patterns and templates. Delivery Practices & Collaboration Use git fluently in a team setting (branches, pull requests, code reviews). Contribute to maintainable, supportable solutions on an internal hosting platform; collaborate with platform/IT partners as needed. Follow good documentation and change practices appropriate to regulated and non-regulated use, ensuring solutions are understandable and auditable when required.
Requirements
- Bachelor’s degree (or higher) in Data Science, Statistics, Computer Science, Engineering, or related field (or equivalent practical experience).
- Strong data science fundamentals: Basic statistics and experimental reasoning Data wrangling and exploratory analysis Model building and evaluation.
- Strong Python skills for both analysis and application development.
- Familiarity with basic SQL fundamentals is required.
- Experience building user-facing applications using Flask (templates/Jinja) and familiarity with basic front-end concepts (HTML/CSS/JavaScript).
- Comfort working with diverse, imperfect datasets and iterating toward robust solutions.
- Strong collaboration and communication skills in a cross-functional environment.
Nice To Haves
- Familiarity with FastAPI and API design concepts (can be learned on the job if needed).
- Experience supporting software or analytics in regulated/GMP-like environments (validation mindset, documentation discipline, traceability).
- Exposure to manufacturing, pharma, chemical, or other industrial process data.
- Knowledge of Azure services and/or identity concepts (e.g., Entra ID) is a plus but not required.
- Familiarity with containerization/DevOps practices (e.g., Docker, CI/CD) is helpful.
Responsibilities
- Build and maintain internal web applications that make analytics usable in day-to-day workflows.
- Develop services using Python with Flask (and/or FastAPI where appropriate), including: Lightweight APIs for data access and model execution User-facing interfaces using Flask + Jinja, with small amounts of JavaScript and optionally React for richer interactions.
- Implement pragmatic software engineering practices (modular design, testing, logging/monitoring hooks, clear documentation) aligned to intended use (GMP vs non-GMP).
- Apply strong fundamentals in statistics, data extraction + cleaning, and modeling to diverse manufacturing datasets (e.g., batch/process time series, quality data, laboratory and instrument outputs).
- Develop, evaluate, and document models intended to support insights into manufacturing performance in a GMP environment, focusing on interpretability and lifecycle considerations.
- Collaborate with engineers, scientists, and quality partners to define the problem, select fit-for-purpose methods, and translate outcomes into operational decisions.
- Communicate findings clearly to technical and non-technical stakeholders; create reusable analysis patterns and templates.
- Use git fluently in a team setting (branches, pull requests, code reviews).
- Contribute to maintainable, supportable solutions on an internal hosting platform; collaborate with platform/IT partners as needed.
- Follow good documentation and change practices appropriate to regulated and non-regulated use, ensuring solutions are understandable and auditable when required.
Benefits
- medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance.
- consolidated retirement plan (pension) and savings plan (401(k)).
- long-term incentive program.
- Vacation –120 hours per calendar year
- Sick time - 40 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
- Holiday pay, including Floating Holidays –13 days per calendar year
- Work, Personal and Family Time - up to 40 hours per calendar year
- Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
- Condolence Leave – 30 days for an immediate family member: 5 days for an extended family member
- Caregiver Leave – 10 days
- Volunteer Leave – 4 days
- Military Spouse Time-Off – 80 hours
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
