Sr. Manager, Quality - Data Scientist

Key Skills

Aartificial intelligence, Analytical and Problem solving, Data Analytics, Data Mining, Data science techniques, Data Visualization, Effective communication skills, Forecasting, KPIs, Machine learning techniques, Microsoft Office suites, Microsoft-Excel, Natural Language Processing (NLP), PowerBI, Project management, Python Programming, R Programming, SAS, SQL, Web Analytics

Job Description

Everything we do, every day, is in line with an unwavering commitment to the quality and the delivery of safe and effective products to patients. Our science and risk-based compliant quality culture is flexible, innovative, and customer oriented. Whether you are involved in development, maintenance, compliance or analysis through research programs, your contribution will directly impact patients.

ROLE SUMMARY

• The Senior Manager, Quality - Data Scientist supports data-driven decision-making processes, generating insights and providing strategic guidance for 1) high quality, effective, efficient RQA Programs and 2) to accelerate and drive the RQA audit strategy across Good Practice (GxP) processes/audit universe (e.g., GCP, PV, Regulatory, Medical, GMP, GLP, Digital).
• Focus areas are related to 1) Risk Assessment; 2) Analytics to support audit planning/conduct and integrate data analytics in GxP audits; 3) State of control reporting; 4) Data integrity and forensic auditing; and 5) Leader Dashboards to support risk management, quality strategy, GxP audit strategy and governance goals/objectives.
• This position requires 1) expertise in forecasting, statistical analysis, real world data analysis, digital tools and data analytics. 2) Provides data science and quantitative analytical support for ensuring high quality state of control reports for GxP.
• Works with business leads for GxP and inspection management to lead Data Science projects and innovation and ensure optimum utilization of resources in consultation with Director, Quality Data & Analytics Team lead/ RQA Leadership team. Independently manage small to large projects. Additionally, mentors and supports development/oversight of manager roles (Data and Analytics)
• Enhances data science services to support GxP audit pillars and inspection management – consulting, advisory services, SME, end-user proficiency and adoption with self-service analytical tools and upskilling of audit functions/pillar in digital & analytics.
• Engineers key data science analytical insights into simple, intuitive and well-designed tools and services tailored for GxP audit pillars.
• Follows the operational model and plan projects meticulously. Build strategic and structural connects with functions to make data science capabilities visible and to improve them.
• The Senior Manager, Quality - Data Scientist collaborates with cross-functional teams and utilizes advanced analytical techniques to enhance performance and drive optimal support to audit and other enterprise leaders.

ROLE RESPONSIBILITIES

Digital Strategy / Data Science

• Supports vision for data/analytics roadmap, solving complex data problems across the quality/risk management continuum.
• Defines and develops data science infrastructure and capabilities including data lake build; data lake co-ownership to ensure robust/validated technical process.
• Contributes to the design and execution of a hypothesis driven analytics strategy across quality business lines that ensures a strategic, optimized and consistent approach (data standards) to metrics, thresholds, etc. that meet stakeholder needs.
• Works with QMS Oversight and analytics team to develop and construct complex analytics (KRIs / KPIs / other); communicates findings/insights/trends to applicable functions.
• Review data/trends in support of QMS oversight to determine impacts and needed oversight actions based on elevated issues/trends.
• Use analytics to generate insights that will strengthen oversight via audits; integrate data analytics in GxP audits.
• Drives data analytics for continuous monitoring of GxP areas and support of data integrity & forensic audit approach; leverage analytics and machine learning to check for data quality, detect outliers and anomalies, or identify and prioritize high-risk patterns.
• Designs/builds (and/or assesses validity of existing L1) predictive models (for risk/quality management) including POC, ROI, to support risk assessment & oversight decisions.
• Assesses and ensures data quality / validation procedures including documentation, storage (per policies).
• Leads the implementation of technology advancements including NLP, AI, etc. (including external benchmarking to pharma and other tech advanced companies)
• Designs processes to ensure integration data are connected to Risk Strategy processes.
• Provides objective assessments to assist leadership in prioritizing investments in data-science capabilities/projects.
• Assists GxP audit teams in exploring methodologies to enhance audit strategy based on emerging innovation and technology advancements.
• Manages and maintains dashboards and reports to support the business.
• Support strategy to “up-skill” colleagues as applicable to ensure data-culture and data-focused mindset.

Operational Excellence

• Accountable for timely design and delivery of the digital / data science strategies.
• Accountable for ensuring validation/ controls are in place to support data science capabilities and models.
• Collaborates with RQA leadership, peers and internal stakeholders to drive alignment and execute purposeful digital and analytics strategy.
• Works to ensure quality standards are consistently applied across the program or region.
• Proactively identifies and drives opportunities for improvement within RQA.
• Maintains current knowledge of industry trends that impact data science capabilities and strategies.
• Monitors and maintains expertise in area(s) of focus.

QUALIFICATIONS

• Advanced academic qualification/degree in data science / statistics / computer science /other applied quantitative disciplines is required; equivalent relevant professional experience will be considered.
• 8+ years of relevant experience in data science and analytical tools/techniques/technologies.
• Familiarity with standard supervised and unsupervised machine learning approaches.
• Ability to contribute to an AI/ML/data science pipeline including the various steps of data retrieval, cleaning, analysis/modeling, application of AI algorithms through to production.
• Technical skills and experience using relational databases (e.g., MS SQL Server) and data visualization tools (e.g., Spotfire, Microsoft Power BI, Tableau)
• Proficiency in the use of Microsoft Office Suite of tools.
• Understanding of regulatory requirements and relevant data standards.
• Strong communication (written and oral), decision-making, influencing, negotiation, and project management skills.
• Project management experience with proven accountability, and demonstrated excellent interpersonal, communication, negotiation, influencing, and problem-solving capabilities a plus.
• Ability to function autonomously in a matrix model and in a team environment.
• Proven ability to think innovatively and to execute strategic plans pursuant to the responsibilities of the role.

PREFERRED QUALIFICATIONS AND EXPERIENCE

• Knowledge of Good Practice (GxP) processes/audit universe (e.g., GCP, PV, Regulatory, Medical, GMP, GLP, Digital).
• Relevant experience in a pharmaceutical, biotech, CRO, or Regulator Agency with an emphasis on building reporting and analytics solutions.
• 2-3 years-experience working in AI/ML, Python/R fluency.

SKILLS & COMPETENCIES:

• Strong analytical thinking and problem-solving skills with the ability to analyze complex data sets and draw meaningful conclusions.
• Proficiency in statistical analysis techniques, predictive modelling and forecasting methodologies.
• Strong project management skills and the ability to work independently or as part of a team.
• Solid understanding of digital analytics tools and platforms.
• Strong communications skills with the ability to present complex information to non-technical stakeholders in a clear manner.
• Strong business acumen and strategic thinking, with the ability to translate analytical finding into actionable insights and recommendations.

SKILL-SETS:

• Data Analysis
• Data Analytics
• Data visualization
• Data mining
• Strategic thinking
• Problem Solving
• Communication
• Analytical Skills
• Applied Mathematics
• Data Science
• Forecasting
• Predictive Modelling
• Statistical Analysis
• Web Analytics
• SQL
• Python (Programming language)
• Artificial Intelligence and Machine Learning
• Microsoft Power BI
• Microsoft Excel

Work Location Assignment: Flexible

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.