This role requires candidates who are currently authorized to work in the U.S. without sponsorship, and C2C arrangements are not accepted. EST hours are required. 

GENERAL POSITION SUMMARY:Utilizes data analytics skills and tools to analyze data systems and procedures to recommend and implement strategic process improvements with an aim to enable the Quality organization to expand and improve data collection, analysis, and interpretation. This role will support a quality analytics center of excellence, driving progressive quality strategies and programs as the organization continues to grow and evolve in a dynamic and innovative way.

The individual will support developing and delivering integrated, cross-modality, and cross-GxP creative machine learning solutions that contribute meaningfully to enhance QMS insights and evaluation of the health of core QMS systems, among others.

Nice to Haves:

• Very advanced analytics role

• Machine learning experience

• NLP experience

• Experience with Power BI, Python

• Having a pharma background is ideal but not necessary

RESPONSIBILITIES:Key responsibilities include but are not limited to:

• Design, develop, and maintain user-friendly data visualizations and dashboards using complex datasets from different sources.

• Collaborate with a Quality analytics team and cross-functional partners to conceptualize and deploy advanced analytics solutions for business problems using Machine learning (NLP, classification, etc.) and other statistical models.

• Create ad-hoc data models, reports, and analyses as needed to support business requirements.

• Leverage deep technical and analytical expertise to understand critical business opportunities and generate insights for action.

• Continuously explore and evaluate new methods to improve the way data analytics is used to create value.

REQUIRED KNOWLEDGE, SKILLS, AND COMPETENCIES:Key Technical Knowledge, Skills, and Competencies:

• Demonstrated ability to turn data into information that helps drive decisions.

• 3+ years of experience developing and/or applying ML/NLP solutions in an industry or academic context.

• Expertise in programming languages (e.g., Python, R, SQL, JavaScript), version control, and other data science-related tools (e.g., R, D3, AWS, Snowflake, dbt).

• Expertise in working with natural language data and building text-based products, using both classic and state-of-the-art NLP techniques (e.g., text mining, word embeddings, transformer-based models).

• Strong data visualization skills and experience with relevant tools (e.g., Spotfire, Power BI, and/or Tableau).

• Experience with statistical/analytical methodologies and algorithms (e.g., classification, regression, clustering, feature selection/engineering, deep learning, time-series analysis, network analysis, hypothesis testing).

• Exceptional communication skills and ability to present findings to non-technical audiences.

• Strong problem-solving and critical thinking skills, accompanied by analytical thinking/data analysis skills required to make sound decisions.

PREFERRED EDUCATION AND EXPERIENCE:

• M.S. (or equivalent degree) in a quantitative field such as Statistics, Biostatistics, Econometrics, Economics, Data Science and 5+ years of relevant work experience, or B.S. (or equivalent degree) and 7+ years of relevant work experience, or a relevant comparable background.

• Demonstrable experience in the pharmaceutical, biotechnology, or device industry solving business and/or compliance challenges through the application of analytic approaches is strongly preferred.