R&D AI Data & Content Generation Data Scientist - RDT Pharma R&D

Roche•Mississauga, ON

1d•CA$115,328 - CA$151,368•Onsite

About The Position

At Roche, we foster a culture where individuality is embraced, and personal expression, open dialogue, and genuine connections are encouraged. We value, accept, and respect everyone for who they are, enabling personal and professional growth. Our mission is to prevent, stop, and cure diseases and ensure universal access to healthcare. The Clinical Submission Data and Content Generation & Reuse function is dedicated to modernizing the creation and management of clinical data and regulatory submission assets. This involves developing and deploying platforms for structured content management to facilitate the reuse of approved components across documents. Additionally, this group is at the forefront of utilizing agentic AI to aid in the generation, review, and assembly of complex submission assets, with the goal of enhancing quality and reducing authoring timelines. The Senior IT Data Scientist role is pivotal in leading, developing, and implementing data-driven solutions for complex business challenges. This position requires the ability to independently identify analytical opportunities, conduct thorough data exploration and analysis, and build, test, and deploy predictive models using various machine learning techniques. The successful candidate will manage projects from their inception through to deployment, utilizing strong programming, statistical modeling, and data visualization skills, while effectively communicating findings to both technical and non-technical stakeholders. Working within a highly regulated GxP environment, this role involves building specialized AI agents to support Analytical Data Scientists throughout the clinical data lifecycle, necessitating a deep understanding of advanced generative AI and Graph-based Retrieval-Augmented Generation (GraphRAG). The role balances hands-on technical work with leadership responsibilities, contributing significantly to the team's technical roadmap. Key responsibilities include identifying analytical and automation opportunities and owning projects from start to finish.

Requirements

B. Sc or M.Sc. in Data Science, Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
5 to 7+ years of industrial experience in complex data science/AI engineering projects.
Experience in independently identifying analytical opportunities, conducting in-depth data exploration, and owning projects from inception to deployment.
Proven track record of driving medium-sized projects that influence business decisions and align with strategic objectives.
Proficiency in multiple programming languages and advanced data manipulation.
Strong, in-depth knowledge of advanced statistical methods and machine learning algorithms.
Strong data visualization and statistical modeling skills to support comprehensive data analysis.
Exceptional communication skills, with the ability to present complex findings clearly to various stakeholders, including non-technical audiences.
Strong collaborative capabilities to effectively engage with broader business units to understand and meet data needs.

Nice To Haves

Deep understanding of advanced generative AI.
Experience with Graph-based Retrieval-Augmented Generation (GraphRAG).

Responsibilities

Leads the development and deployment of models.
Works independently on specific data science projects from start to finish.
Leads the analysis of complex business and data problems, performs thorough domain research, and drives root cause analysis.
Identifies and solves intermediate to complex data challenges while collaborating on data validity to ensure accuracy with minimal supervision.
Accountable for delivering comprehensive requirements that bridge business needs with technical data capabilities.
Engages with broader business units to clearly understand and meet their data needs.
Presents analytical findings and insights to various stakeholders, including non-technical audiences.
Drives medium-sized projects that directly influence business decisions.
Ensures that projects are closely aligned with broader business objectives and strategies.
Handles larger, more complex datasets.
Develops new predictive models from scratch and optimizes existing ones to improve performance.
Demonstrates a conceptual understanding of business and technical domains, technologies, and their interdependencies.
Applies proficiency in requirements gathering, data structures, usability, and process analysis to manage interconnections and improve overall efficiency.
Leverages a strong functional knowledge of advanced statistical methods, machine learning algorithms, and agentic AI capabilities to address business questions without requiring direct hands-on model deployment or coding.