Data Scientist II, BIA GPS India Operations

6 days ago


Hyderabad, Telangana, India Bristol Myers Squibb Full time

Summary

The Data Scientist II will play a crucial role in supporting operational analytics across GPS, leveraging a blend of traditional Machine Learning (ML) and emerging Generative AI (Gen AI) techniques. This role will ensure products continue to serve the most pressing GPS analytics needs, with potential opportunities to build new advanced analytics capabilities like predictive modelling, simulation, and optimization.

The ideal candidate possesses a strong interest in solving business problems and an eagerness to work on all parts of the analytics value chain, from partnering with IT on data pipelines to operationalizing models for the benefit of patients worldwide.

Roles & Responsibilities:

  • Conduct analysis and interpretation of complex data sets to derive meaningful insights and recommendations, leveraging both traditional ML and Gen AI techniques where appropriate, based on an understanding of GPS priorities, critical issues, and value levers.
  • Collaborate with stakeholders to identify business problems, goals, and KPIs to design, establish and maintain data pipelines, models, and business-facing reports and dashboards.
  • Design, develop, and implement a broad array of GPS analytics that solve complex problems in a computationally efficient and statistically valid manner, utilizing a mix of traditional ML and Gen AI approaches.
  • Identify and implement enhancement and automation of high-value analytics while ensuring efficient function.
  • Collaborate proactively with IT teams to develop and enhance data infrastructure, data pipelines, and analytical tools for efficient data collection, processing, and analysis.
  • Prepare reports, dashboards, and presentations to communicate analyses to stakeholders at various levels of the organization, effectively explaining both traditional ML and Gen AI concepts.
  • Follow technical best practices in building, maintaining, and enhancing analytics output with scalable solutions, including code version control, pipeline management, deployment, and documentation.
  • Provide training, guidance, and mentorship to junior analysts and team members when required.
  • Work hours that provide sufficient overlap with standard East Coast US working hours.

Skills and competencies:

Machine Learning & Artificial Intelligence:

  • Strong analytical thinking and problem-solving skills with the ability to analyze complex data sets and draw meaningful conclusions using both traditional ML and Gen AI techniques.
  • Experience with Open AI, Hugging face, Semantic Kernel, Langchain LLaMa2 etc.
  • Proficiency in statistical analysis techniques and methodologies, including experience with relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).

Data Management & Analytics:

  • Agile problem-solving ability and desire to learn new things and continuously improve.
  • Solid understanding of digital analytics tools and platforms and version control systems (e.g., dbt, Airflow, Git, GitHub).
  • Experience working with large datasets, data visualization tools (e.g., Tableau), statistical software packages (R, Python), and advanced SQL.

Communication & Collaboration:

  • Strong business acumen and strategic thinking, with the ability to translate analytical findings into actionable insights and recommendations.
  • Strong communication skills with the ability to present complex ML and Gen AI information to non-technical stakeholders in a clear manner.
  • Strong project management skills and the ability to work independently or as part of a team.

Experience:

  • Bachelor's or Master's degree in an analytical, engineering, operations research or scientific discipline.
  • Proven experience (typically 3-5 years) in a data and analytics role, including direct development experience in building and deploying ML and/or AI models.

Additional Information:

  • Experience with major GPS applications (SAP, Oracle, LIMS, Infinity, MES) is a plus.
  • Experience in the biopharma industry (product development, manufacturing, supply chain, and quality control) is a significant plus.


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