The Klick Group—comprising Klick Health (including Oxford PharmaGenesis, Klick Katalyst, and btwelve), Klick Media, Klick Applied Sciences (including Klick Labs), and Klick Consulting)—is an ecosystem dedicated help life sciences brands achieve their full potential through best-in-class marketing and advertising, media, medical affairs and communications, market access, real-world evidence, and technology and analytics consulting — powered by 500+ in-house medical experts and award-winning data science and AI capabilities. Founded in 1997, we have offices in Toronto, New York, Oxford, London, Cambridge, Cardiff, Melbourne, Philadelphia, Saratoga Springs, São Paulo, and Singapore. One of the most-awarded health agencies on the planet, Klick is consistently recognized for its people-first culture as a Great Place to Work, Best Workplace for Women, Best Workplace for Inclusion, Most Admired Corporate Culture, and FORTUNE Best Workplace in Advertising. Klick also recently made history as Cannes Lions Healthcare Agency of the Year, Healthcare Network of the Year, and Independent Agency of the Year – Health.

About our Omnichannel Enablement Craft

Our Omnichannel Enablement Craft connects channels, data, and technology into unified experiences. The team ensures audiences encounter consistent, coordinated messaging across touchpoints. By aligning media and platforms, they support seamless journeys. Their work enhances effectiveness and measurement across the ecosystem.

The Data Solutions Consultant designs, develops, and deploys machine learning models and scalable data solutions that support advanced analytics and omnichannel marketing initiatives for Klick's clients. As part of the Data Solutions team within Omnichannel Enablement, the role combines hands-on expertise in Python, SQL, ETL pipelines, statistical modeling, and machine learning to transform complex datasets into actionable business insights. This individual collaborates with data engineers, analysts, project managers, and client stakeholders to deliver reliable, reproducible analytics solutions that support measurable business outcomes.

What You'll Do

• 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.

Required:

• 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 examples of 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 demonstrated 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, with demonstrated ability to document results, identify limitations, and support reproducible analytical workflows.

Desired:

• Comfort and enthusiasm for using AI as a regular part of how work gets done.
• Experience delivering analytics or machine learning solutions within healthcare, pharmaceutical, life sciences, media, advertising, or agency environments, including marketing analytics or payer analytics datasets.
• 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, with examples of 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.

This posting is for a newly created role at Klick.

The base salary range for this position is between CAD $75,000 - $85,000. The final amount offered will be determined based on several factors such as a candidate's work location, their unique skill set, education, and prior work experience. This is a hybrid role based in Klick's Toronto office.

#LI-TH1 #LI-Hybrid

Our Commitment to Inclusion

Klick is consciously creating a culture where everyone can thrive and grow in their careers. We believe that our best work comes from our diverse backgrounds, perspectives, and skills. We strongly encourage members of historically underrepresented communities to apply, including Black people, Indigenous peoples, and other people of color, people with disabilities, people from gender and sexually diverse communities and people with intersectional identities. We're also committed to developing an inclusive, barrier-free recruitment process and work environment. Should you require any accommodation, please contact us at [email protected] and we will work with you to meet your accessibility needs and ensure you have a positive experience.

Klick uses an AI-powered tool as part of an automated process to support our hiring process by analyzing your experience, skills, and qualifications to help identify alignment with role requirements. Please note that the tool does not make final decisions or automatically disqualify candidates. Hiring decisions are made by our team, with thoughtful human judgment and oversight. We are committed to fair and transparent hiring practices and have implemented safeguards to help mitigate bias and support compliance with applicable laws. If you have questions, accessibility needs, or concerns about the use of this tool, please contact us.