Freelance Data Scientist, ad hoc

Klick Health

4d•Remote

About The Position

As a Freelance Data Scientist, this role supports Klick Consulting by converting complex healthcare, commercial, and marketing data into clear narratives and practical recommendations for clients. The role partners with data scientists, strategists, consultants, and senior stakeholders to define business questions, select appropriate methods, execute analyses, and communicate findings. This freelance position is based in Ontario, is 100% remote, and does not require travel.

Requirements

Undergraduate degree in a computational, scientific, or health-related field, e.g., statistics, mathematics, bioinformatics.
Demonstrated experience analyzing structured or unstructured data, including observable understanding of bias, error, confounding, power, and significance.
Hands-on experience using Python data analysis tools such as NumPy, pandas, matplotlib, or scikit-learn, plus SQL for data extraction or analysis.
Working familiarity with git, GitHub, and command-line workflows to document and collaborate on analysis scripts.
Experience translating technical analysis into written or verbal recommendations for cross-functional stakeholders.
Ability to independently scope, execute, and explain smaller analysis workstreams, while collaborating with data scientists, consultants, and strategists on larger projects.
Practical experience using AI tools to accelerate technical work, including validation, maintainability, and reliability.
Comfortable working with ambiguous or evolving business questions, making assumptions explicit, and adapting to new context.

Nice To Haves

3+ years of professional experience in analytics, data science, or applied research outside a purely academic context.
Experience analyzing real-world data (RWD), e.g., healthcare administrative claims, EHR data, or clinical outcomes.
Familiarity with AWS, Google Cloud Platform, Microsoft Azure, or other cloud-based analytics environments.
Graduate degree in data science, statistics, bioinformatics, or a related quantitative field.
Experience applying advanced analytic methods and technologies to answer business or clinical questions, such as natural language processing, hierarchical Bayesian modeling, Markov chain Monte Carlo, and generative AI.

Responsibilities

Design data science approaches that balance client business goals with statistical, technical, and data constraints.
Python data analysis workflows using tools such as pandas, NumPy, matplotlib/plotly, scikit-learn, SQL, git, and GitHub.
Analyze healthcare, marketing, commercial, clinical, or utilization data using methods such as natural language processing and free-text analysis, clustering, geospatial analysis, descriptive statistics, and predictive modeling.
Translate technical findings into clear data stories, visualizations, and client-ready recommendations for cross-functional stakeholders.
Support and own experimental design, data analysis workstreams, and documentation across consulting engagements.