Data Science and AI Solutions Developer (Sr Manager or Associate Director)

Key Skills

Aartificial intelligence, Analytical and Problem solving, AWS, Data Modeling, Data science techniques, Machine learning techniques, Microsoft-Excel, Python Programming, R Programming

Job Description

We are seeking an experienced Data Science and AI Solutions Developer to join an exceptional team that creates advanced analytical solutions to support decision-making in pharma development and portfolio strategy. This position will provide hands-on data science and machine learning engineering support of an end-to-end forecasting platform, primarily for revenue with potential expansion to cost. The platform will support forecasting teams in building models, aggregating evidence, and consolidating data for in-line / pipeline, short- / long-term forecasts. This role will report to the Forecasting & Integration Lead, or the Forecasting Solutions Architect. In addition, there will be multiple opportunities to collaborate on projects outside of forecasting within the broader DS/AI Portfolio & Development team, including development operations, pipeline, portfolio, and ecosystem solutions.

Key Responsibilities

Forecasting solution building:

• Create robust, scalable forecasting models, incl. machine learning (ML) algorithms, and centralized data platforms.
• Model factors such as epidemiology, patient flow, competitive dynamics, pricing trends and loss of exclusivity.
• Stay informed about advancements in pharma forecasting methodologies and tools.

Collaboration:

• Engage key stakeholders to understand their needs and translate them into technical specifications.
• Work closely with data scientists and domain experts to ensure compatibility of forecasting solutions with other tools.
• Collaborate with the DS/AI Strategy and Process Design Lead to develop solution overviews.
• Collaborate with domain leads in the DS/AI Portfolio & Development team on select projects beyond forecasting.
• Work with IT as needed on data management related to forecasting platforms and AI solutions.

Data analysis and modeling:

• Analyze forecast input data (incl. sales, epidemiology, competition) to assess quality and pre-processing needs.
• Develop ML models to support aggregation of forecasting assumptions while accounting for uncertainty.

Solution deployment:

• Deploy forecasting solutions, striving for seamless integration with existing systems.
• Collaborate with IT to optimize data pipelines and establish efficient data management practices.

Optimize forecasting performance:

• Continuously monitor and evaluate the performance of forecasting models, including validation of ML models.
• Identify opportunities to enhance the business impact of forecasting models, such as quality and efficiency.

Technical documentation:

• Document specifications (e.g., architecture, data flows, algorithms) to ensure transparency and reproducibility.
• Keep documentation up to date as solutions are optimized or expanded.

Qualifications & Experience

Education and experience:

• Bachelor's or Master's degree in Computer Science, Engineering, Applied Math, Bio Informatics, Operations Research or equivalent working experience in a highly analytical field
• For Senior Manager: 3+ years of experience working as a Solutions Developer or similar role, preferably in pharma
• For Associate Director: 5+ years of experience working as a Solutions Developer or similar role, preferably in pharma

Technical knowledge:

• In-depth experience in statistical analysis, machine learning, and data modeling
• In-depth experience using programming languages such Python, R, or similar
• Experience with spreadsheet models including Excel VBA, and preferably PyXLL
• Experience with data manipulation, analysis, and querying using SQL or similar
• Experience with cloud platforms such as AWS
• Preferably, experience with pharma forecasting techniques such as demand vs epi-based, baselining, event modeling
• Preferably, experience with time series analysis and simulation
• Preferably, experience with off-the-shelf forecasting platforms

Domain knowledge:

• Deep interest in the drug development and commercialization process
• Preferably, experience with pharmaceutical industry analytics incl. data sources, market research, sales data, or real-world data

Analytical problem-solving:

• Excellent problem-solving and analytical skills, with the ability to apply different approaches to technical challenges