Data Scientist,Advanced Analytics & Commercial Effectiveness Job Mississauga area,Ontario Canada,IT/Tech

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform to connect, work at pace and challenge perceptions. That’s why we work, on average, a minimum of three days per week from the office. But that doesn’t mean we’re not flexible. We balance the expectation of being in the office while respecting individual flexibility.

Join us in our unique and ambitious world.

Introduction to role:

Are you ready to bring publication-grade statistical difficulty and AI-native analytics together to uncover hidden patients, elevate commercial strategy, and improve outcomes for people living with rare diseases? In this role, you will turn sophisticated, de-identified healthcare data into decisions that sharpen field execution, optimize investment, and ultimately reach those who need therapies most.

You will join a fast-moving analytics team that pairs deep statistical expertise with modern machine learning and Snowflake Cortex AI to accelerate model development without compromising interpretability or compliance. From patient identification and adherence prediction to marketing effectiveness and causal impact, you will deliver models that are trusted by leaders and used by teams every day. Do you thrive at the intersection of analytical depth and real-world impact?

Accountabilities:

Statistical Authority:
Act as the go-to expert to set analytical standards across hypothesis testing, regression, inference, and experimental design; ensure outputs meet publication-grade rigor with clear assumptions, diagnostics, and power.

Predictive Modeling:
Design, validate, and deploy models using XGBoost, LightGBM, Random Forest, SVM, neural networks, and ensembles; address class imbalance with robust evaluation and calibration to drive precise commercial actions.

Time-to-Event Analytics:
Build survival models (Cox, AFT, competing risks) to predict adherence, discontinuation, and patient lifetime value that inform proactive interventions.

Forecasting:
Create and maintain ensemble time-series frameworks (ARIMA, Prophet, exponential smoothing, gradient-boosted) to guide demand planning, revenue scenarios, and launch-readiness decisions.

Causal Impact:
Design A/B tests and apply quasi-experimental methods (DiD, PSM, synthetic control, IV, RDD) to quantify the true effect of commercial initiatives on prescribing and patient outcomes.

Marketing Mix Optimization:
Develop Bayesian MMM to estimate channel-level return on investment and response curves; recommend promotional reallocations that improve impact across personal and non-personal channels.

Next-Best-Action Engines:
Build and refine HCP-level recommendation systems using contextual bandits, collaborative filtering, and reinforcement learning; integrate daily actions into Veeva CRM.

Patient Identification:
Train supervised classifiers on claims, labs, and specialty pharmacy data to prioritize likely undiagnosed patients and direct field resources where they matter most.

Adherence and Retention:
Deploy models that detect early risk signals from dispense intervals, hub interactions, and scheduling patterns to reduce discontinuation.

Segmentation and Targeting:
Construct HCP and patient segments using clustering and NLP-enriched profiles to focus engagement and tailor messaging.

Competitive Intelligence:
Create real-time switching surveillance models from claims and formulary data to anticipate market dynamics and inform agile responses.

Agent-Assisted Development:
Use Snowflake Cortex AI and AI coding agents to speed prototyping and feature engineering while retaining full human-led statistical validation.

Validation and Hallucination Detection:
Build guardrails and evaluation suites that stress-test agent outputs, catch plausible-but-wrong reasoning, and prevent flawed insights from reaching decisions.

Agent Tuning and Evaluation:
Design domain-specific prompts, benchmarks, and feedback loops to continuously improve agent analytical performance.

HIPAA-Compliant Data Operations:
Work exclusively with de-identified patient-level data; implement minimum-necessary access and maintain…

Data Scientist, Advanced Analytics & Commercial Effectiveness