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Amaris Consulting | Part of Mantu

Pharmaceutical Data Scientist

Toronto, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Nov 5, 2026
Experience: 3–7 years of experience as a Data Scientist, preferably in the pharmaceutical, biotech, life sciences, or healthcare sectors.
Posting language: English
Posted: Oct 6, 2026

Original job description

Job Description

We are seeking a highly skilled Data Scientist to join our pharmaceutical analytics and digital innovation team. This role plays a key part in transforming scientific, clinical, manufacturing, and commercial data into actionable insights that accelerate drug development, optimize production processes, and improve patient outcomes.

The ideal candidate combines strong analytical expertise, solid experience working with complex datasets, and a deep understanding of pharmaceutical or life sciences environments.

Key Responsibilities

Data Analytics & Modeling

Develop, validate, and deploy predictive and machine learning models to support R&D, clinical trials, manufacturing, and commercial operations.
Analyze large and heterogeneous datasets (clinical, real-world data, lab data, manufacturing data, supply chain).
Perform exploratory data analysis (EDA) and communicate insights to scientific and business stakeholders.
Implement statistical modeling, hypothesis testing, and time-series forecasting as required.
Build dashboards, reports, and visual insights to support decision-making.

Pharma-Specific Activities

Support teams across R&D, clinical development, quality, manufacturing, and regulatory.
Ensure compliance with GxP, data integrity, and internal data governance standards.
Collaborate with SMEs, clinicians, biostatisticians, and lab scientists to interpret results.

Data Engineering & Infrastructure

Work closely with data engineers to ensure high-quality, well-structured datasets.
Develop automated pipelines for data ingestion, cleaning, transformation, and modeling.
Leverage cloud platforms (AWS, Azure, GCP) for scalable model training and deployment.

Cross-functional Collaboration

Communicate results to scientists, technical teams, and leadership.
Contribute to the development of best practices in data science, documentation, and reproducibility.
Support digital innovation initiatives, AI-driven solutions, and automation projects.

Requirements

Education & Experience

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Bioinformatics, or related field.
3–7 years of experience as a Data Scientist, preferably in the pharmaceutical, biotech, life sciences, or healthcare sectors.

Technical Skills

Strong programming skills in Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch).
Experience with SQL and relational databases (PostgreSQL, SQL Server, Oracle).
Experience building and deploying machine learning models.
Familiarity with cloud-based ML environments (AWS Sagemaker, Azure ML, GCP Vertex AI).
Solid understanding of statistics, experimental design, and data modeling.
Experience working with large datasets, ETL pipelines, and data processing frameworks.

Pharma / Life Sciences Skills (Highly Preferred)

Knowledge of GxP, data integrity, and regulatory frameworks.
Familiarity with clinical trial data, lab systems (LIMS), quality systems, or manufacturing datasets (MES, SCADA, historians).
Experience with real-world data (RWD) or real-world evidence (RWE) is an asset.

xpected Compensation Range:

50K-100K The final compensation offered will be determined based on the candidate’s level of experience, skills, and qualifications, in compliance with applicable pay transparency requirements.

Canadian Experience Requirement:

No Canadian work experience is required for this position. Candidates are encouraged to apply regardless of previous Canadian experience.

Artificial Intelligence (AI) Disclosure:

No Artificial Intelligence (AI) tools are used in the screening, assessment, or selection of candidates for this position. All stages of the recruitment process are conducted by human recruiters and hiring managers.

Statement Regarding Job Vacancy:

This position is a Job creation, created to support ongoing project needs.

Recruitment Process & Feedback Timeline:

Candidates will receive feedback on their application within a maximum of 45 days from the date of application or from their most recent interview stage.

Why choose us

An international community bringing together more than 110 different nationalities
An environment where trust is central: 70% of our leaders started their careers at the entry level
A strong training system with our internal Academy and more than 250 modules available
A dynamic work environment that frequently comes together for internal events (afterworks, team buildings, etc.)

Amaris Consulting promotes equal opportunities. We are committed to bringing together people from diverse backgrounds and creating an inclusive work environment. In this regard, we welcome applications from all qualified individuals, regardless of sex, sexual orientation, race, ethnicity, beliefs, age, marital status, disability, or other characteristics.

Who are we?

Amaris Consulting, part of Mantu is an independent technology consulting firm providing guidance and solutions to businesses. With more than 1,000 clients across the globe, we have been rolling out solutions in major projects for over a decade – this is made possible by an international team of 7,600 people spread across 5 continents and more than 60 countries. Our solutions focus on four different Business Lines: Information System & Digital, Telecom, Life Sciences and Engineering. We’re focused on building and nurturing a top talent community where all our team members can achieve their full potential. Amaris is your steppingstone to cross rivers of change, meet challenges and achieve all your projects with success.

At Amaris, we strive to provide our candidates with the best possible recruitment experience. We like to get to know our candidates, challenge them, and be able to give them proper feedback as quickly as possible. Here's what our recruitment process looks like:

Brief Call: Our process typically begins with a brief virtual/phone conversation to get to know you! The objective? Learn about you, understand your motivations, and make sure we have the right job for you!

Interviews (the average number of interviews is 3 - the number may vary depending on the level of seniority required for the position). During the interviews, you will meet people from our team: your line manager of course, but also other people related to your future role. We will talk in depth about you, your experience, and skills, but also about the position and what will be expected of you. Of course, you will also get to know Amaris: our culture, our roots, our teams, and your career opportunities!

Case study: Depending on the position, we may ask you to take a test. This could be a role play, a technical assessment, a problem-solving scenario, etc.

As you know, every person is different and so is every role in a company. That is why we have to adapt accordingly, and the process may differ slightly at times. However, please know that we always put ourselves in the candidate's shoes to ensure they have the best possible experience.

We look forward to meeting you!

Apply About employer

More about this job

Responsibilities

Develop and deploy analytical and machine learning models using pharmaceutical, clinical, manufacturing, and commercial data to support drug development, operational optimization, and decision-making. Build data pipelines and visualizations, ensure data integrity and GxP compliance, and collaborate with scientific, technical, and business teams on analytics and digital innovation.

Requirements

A bachelor's or master's degree in data science, computer science, statistics, mathematics, bioinformatics, or a related field is required, along with 3–7 years of data science experience, preferably in pharmaceuticals, biotechnology, life sciences, or healthcare. Candidates should have strong Python and SQL skills, experience with machine learning, statistics, large datasets, ETL, and cloud ML platforms; pharmaceutical knowledge such as GxP, clinical data, or manufacturing systems is highly preferred.

Skills

Python
Machine Learning
Predictive Modeling
Statistical Modeling
Hypothesis Testing
Time-Series Forecasting
Exploratory Data Analysis
SQL
Data Engineering
ETL Pipelines
Cloud Computing
Data Visualization
Pharmaceutical Analytics
GxP Compliance
Clinical Trial Data
Real-World Data

Visa sponsorship

Not detected in the job text

Keywords

Python
Pandas
NumPy
Scikit-Learn
TensorFlow
PyTorch
SQL
PostgreSQL
SQL Server
Oracle
AWS
Azure
Google Cloud Platform
AWS SageMaker
Azure Machine Learning
Google Vertex AI
Machine Learning
Predictive Modeling
Statistical Modeling
Experimental Design
Time-Series Forecasting
Exploratory Data Analysis
ETL Pipelines
GxP
Data Integrity
Clinical Trials
Real-World Data
Real-World Evidence
LIMS
MES

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