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Klick

Marketing and commercialization for life sciences

Data Solutions Consultant

Applied Machine LearningPosted on Nov 10
Full-timeToronto, ON, CanadaCA$75k - CA$85k

About the Job

Requirements

  • At least 3 years of hands-on experience developing, training, evaluating, and deploying machine-learning models, with demonstrated delivery of machine-learning solutions for business or analytical use cases.
  • Professional experience using Python, SQL, and machine-learning libraries such as scikit-learn, TensorFlow, or PyTorch, including data preparation, model development, and analytical workflows.
  • Experience designing ETL pipelines, preprocessing datasets, performing feature engineering, and applying statistical modeling techniques to support machine-learning and advanced analytics deliverables.
  • Experience working with clickstream datasets, data lakes, or large-scale data ecosystems using technologies such as Spark, AWS, GCP, or comparable platforms, with responsibility for data processing or analytical outputs.
  • Experience gathering requirements from non-technical stakeholders or clients and translating business challenges into analytical approaches, technical deliverables, and presentations of findings or recommendations.
  • Experience evaluating machine-learning model performance using appropriate validation methods and performance metrics, documenting results, identifying limitations, and supporting reproducible analytical workflows.

Responsibilities

  • Design, build, and optimize data architectures, ETL pipelines, and feature-engineering workflows using Python and SQL to support machine learning, advanced analytics, and client reporting requirements.
  • Develop, train, evaluate, and deploy machine-learning models using libraries such as scikit-learn, TensorFlow, or PyTorch, applying statistical methods to solve client business challenges and generate actionable insights.
  • Process and analyze clickstream datasets and other large-scale data sources while maintaining and optimizing enterprise data warehouses and data lakes, including platforms such as Snowflake, Spark, AWS, or GCP.
  • Collaborate with data engineers, analysts, project managers, and client stakeholders to gather business requirements, define technical scope, translate analytical findings, and deliver data-driven recommendations.
  • Establish and document reproducible machine-learning and data-engineering workflows, including data validation, model evaluation, version control, and reusable processes that improve solution quality, scalability, and maintainability.

Desired Qualifications

  • Comfort and enthusiasm for using AI as a regular part of work.
  • Experience delivering analytics or machine-learning solutions within healthcare, pharmaceutical, life sciences, media, advertising, or agency environments, including marketing analytics or payer analytics datasets.
  • A Master's degree or Ph.D. in Data Science, Machine Learning, Computer Science, Statistics, or a related quantitative discipline.
  • Experience designing or maintaining relational databases, enterprise data warehouses, or cloud data platforms such as Snowflake, including database structures, data models, or optimization work.
  • Experience developing dashboards or analytical reporting solutions using Power BI or comparable business intelligence platforms to communicate model outputs and business insights.
  • Experience using Git, CI/CD pipelines, or automated testing and deployment workflows to support version control, reproducibility, and ongoing maintenance of machine-learning or data-engineering solutions.

About the Company

Klick

Marketing and commercialization for life sciences

Klick Health is a marketing and commercialization partner for the life sciences industry. It offers services such as marketing, advertising, medical communications, and patient engagement for pharmaceutical, biotechnology, and medical device companies. Klick Health works by delivering integrated solutions that help clients bring new products to market and maximize their commercial success, using data analytics and technology to shape strategies and measure impact. The company differentiates itself through its industry focus on life sciences, its end-to-end services, and its data-driven approach, along with a global expansion beyond strong North American presence. Its goal is to help clients launch products effectively and grow their market impact, while extending its global reach to serve clients worldwide.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Toronto, Canada
Founded
1997

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