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This role requires candidates who are currently authorized to work in the U.S. without sponsorship, and C2C arrangements are not accepted.
GENERAL POSITION SUMMARY:Utilize data analytics skills and tools to analyze systems and procedures in order to recommend and implement strategic process improvements that enhance data collection, analysis, and interpretation across the Quality organization. This role supports a quality analytics center of excellence, contributing to the development of innovative quality strategies and programs as the organization continues to grow and evolve.
This individual will help develop and deliver integrated, cross-functional, and cross-compliance-domain (GxP) machine learning solutions that enhance insights into Quality Management Systems (QMS) and support the evaluation of core QMS health and performance.
RESPONSIBILITIES:Key responsibilities include, but are not limited to:
- Design, develop, and maintain user-friendly data visualizations and dashboards using complex datasets from various sources.
- Collaborate with quality analytics and cross-functional teams to conceptualize and implement advanced analytics solutions using machine learning (e.g., NLP, classification) and statistical modeling.
- Create ad-hoc data models, reports, and analyses to meet business needs.
- Apply deep technical and analytical expertise to identify key business opportunities and generate actionable insights.
- Continuously explore and adopt new methods to enhance data analytics capabilities and create business value.
REQUIRED KNOWLEDGE, SKILLS, AND COMPETENCIES
Technical Knowledge, Skills, and Competencies:
- Demonstrated ability to transform data into meaningful insights for decision-making.
- 3+ years of experience developing and applying ML/NLP solutions in industry or academic environments.
- Proficiency in programming languages (e.g., Python, R, SQL, JavaScript), version control systems, and data science tools (e.g., R, D3, AWS, Snowflake, dbt).
- Experience working with natural language data and building text-based solutions using classic and modern NLP techniques (e.g., text mining, word embeddings, transformer-based models).
- Strong data visualization skills with experience in tools such as Spotfire, Power BI, or Tableau.
- Knowledge of statistical/analytical methodologies and algorithms (e.g., classification, regression, clustering, deep learning, time-series analysis, hypothesis testing).
- Strong communication skills with the ability to present complex findings to non-technical stakeholders.
- Excellent problem-solving, critical thinking, and analytical skills.
PREFERRED EDUCATION AND EXPERIENCE:
- Master’s degree (or equivalent) in a quantitative field such as Statistics, Biostatistics, Econometrics, Economics, or Data Science with 5+ years of relevant experience, or a Bachelor’s degree with 7+ years of relevant experience, or a comparable background.
- Experience in industries such as pharmaceuticals, biotechnology, medical devices, or other regulated environments is strongly preferred, particularly in applying analytics to solve business or compliance challenges.
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