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Added 14 mins ago
Construction Director
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Added 14 mins ago
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Manage construction-related interfaces, scope changes, claims, and disputes in coordination with project management and commercial teams.
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Hays

Senior Manager, Forward deployed Decision Scientist

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Dec 2, 2026
Posting language: English
Posted: Nov 2, 2026

Original job description

Senior Manager, Forward deployed Decision Scientist

Job Type: Permanent

Location: Toronto OR Mississauga; Hybrid (3 days onsite)

Salary: $120,000 - $150,000 + bonus/benefits

Your New Company

Our client is a global biopharmaceutical organisation focused on using science, data and technology to improve patient outcomes. You will join a collaborative Decision Science group supporting a rare disease business, where advanced analytics and responsible AI are used to address complex commercial challenges and underserved patient needs.

Your New Role

As Senior Manager, Forward Deployed Decision Scientist, you will be a hands-on analytics leader partnering closely with commercial teams. You will translate complex business questions into statistical, machine-learning and AI-enabled solutions that strengthen HCP engagement, patient opportunity assessment and commercial effectiveness. You will lead projects from problem definition through model development, validation and implementation, while ensuring privacy, transparency and appropriate model governance.

What You Need to Do

Apply statistical modelling, experimental design and regression techniques to solve commercial business problems and clearly communicate findings, uncertainty and limitations.
Develop, validate and deploy predictive and machine-learning models, including approaches suited to small samples and class imbalance in rare disease.
Use survival analysis, forecasting and causal inference across adherence, patient journeys, demand planning and commercial effectiveness.
Develop advanced analytics solutions for marketing mix optimisation, next-best-action, patient identification, adherence and retention, segmentation and competitive intelligence.
Analyse de-identified healthcare data, including claims, specialty pharmacy, CRM and other real-world datasets, and translate outputs into actionable recommendations.
Use Snowflake Cortex AI and approved AI-assisted development tools to accelerate feature engineering, prototyping and analytical development.
Critically evaluate AI-generated code and analytical outputs for statistical accuracy, reliability and appropriate application.
Apply explainability, bias and fairness assessments, validation, monitoring, documentation and auditability across analytical work.
Lead project milestones, identify risks and dependencies, and partner across Brand, Market Access, Patient Services, Field and other commercial teams.
Communicate complex analytical concepts to technical and non-technical audiences and contribute to peer review, coaching and knowledge sharing.

What You'll Need to Succeed

Bachelor’s degree in Statistics, Biostatistics, Data Science, Econometrics, Applied Mathematics, Computer Science or a related quantitative discipline, or equivalent relevant experience.
Strong hands-on experience in data science, applied statistics or quantitative analytics, including delivery of predictive models or advanced analytics solutions.
Strong foundation in statistical modelling, machine learning, model validation and experimental design.
Proficiency in Python and SQL, including relevant statistical and machine-learning libraries.
Experience with cloud-based data and analytics platforms such as Snowflake, AWS or Azure, or comparable technologies.
Demonstrated ability to translate complex analytical findings into practical commercial recommendations.
Excellent communication and stakeholder-partnership skills across technical and non-technical groups.
Commitment to responsible analytics, patient-data privacy and appropriate model governance.

Preferred experience

Rare disease, specialty pharmaceutical, healthcare or life sciences analytics.
Claims, specialty pharmacy, CRM, EMR/EHR or other patient-level healthcare datasets.
Marketing mix modelling, next-best-action, causal inference, survival analysis or patient identification.
AI-assisted development, LLM evaluation or agent-based analytical workflows.
NLP, deep learning or other advanced machine-learning approaches.
Snowflake/Snowpark, Spark, MLflow, Power BI, Tableau or Qlik.
Healthcare data privacy, model explainability and responsible AI principles.

What You'll Get in Return

You will join a high-impact analytics environment where advanced data science, machine learning and responsible AI are applied to meaningful commercial and patient-focused challenges. The organisation offers a competitive base salary, applicable incentive opportunities, comprehensive benefits, retirement savings support, paid vacation and opportunities to deepen your technical expertise while influencing commercial decisions.

What You Need to Do Now

If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or contact us for a confidential discussion. If this opportunity is not quite right for you but you are considering a new position, please get in touch to discuss your career goals.

This posting is for an existing vacancy with the organisation.

AI may be used to screen, assess or select applicants for the position.

Apply About employer

More about this job

Responsibilities

Lead commercial analytics projects from problem definition through model development, validation, and implementation, applying statistical, machine-learning, and AI-enabled methods to healthcare data. Partner with commercial teams to deliver actionable recommendations while ensuring privacy, explainability, fairness, governance, and clear communication of analytical findings.

Requirements

A bachelor’s degree in a quantitative discipline or equivalent relevant experience is required, along with strong hands-on data science or applied statistics experience and a foundation in modeling, machine learning, validation, and experimental design. Candidates need proficiency in Python and SQL, experience with cloud analytics platforms, strong commercial communication skills, and a commitment to responsible analytics and patient-data privacy.

Skills

Statistical Modeling
Machine Learning
Predictive Modeling
Experimental Design
Regression Analysis
Survival Analysis
Forecasting
Causal Inference
Python
SQL
Snowflake
Healthcare Data Analytics
Model Validation
Responsible AI
Stakeholder Communication
Project Leadership

Benefits

Comprehensive Benefits
Retirement Savings Support
Paid Vacation
Incentive Opportunities

Visa sponsorship

Not detected in the job text

Keywords

Decision Science
Biopharmaceuticals
Rare Disease
Commercial Analytics
Statistical Modeling
Machine Learning
Predictive Modeling
Experimental Design
Regression Analysis
Survival Analysis
Forecasting
Causal Inference
Marketing Mix Optimization
Next-Best-Action
Patient Identification
Patient Adherence
Patient Retention
Claims Data
Specialty Pharmacy Data
CRM Data
Real-World Data
Python
SQL
Snowflake Cortex AI
Snowpark
AWS
Azure
Model Explainability
Bias and Fairness Assessment
Responsible AI

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