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Klick Health

Data Solutions Analyst, Summer 2026

Posted Yesterday
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Hybrid
Toronto, ON, CAN
Internship
Hybrid
Toronto, ON, CAN
Internship
The Data Solutions Analyst Intern develops data pipelines, machine learning models, and analytics workflows, focusing on code quality, analytical rigor, and deployment support.
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Company Description

The The Klick Group—comprising Klick Health (including Klick Katalyst and btwelve), Klick Media Group, Klick Applied Sciences (including Klick Labs), Klick Consulting, and Klick Ventures—is an ecosystem dedicated to realizing the full potential of our people and clients in life sciences. Founded in 1997, we have offices in New York, Philadelphia, Saratoga Springs, Toronto, London, São Paulo, and Singapore. Consistently named a Best Managed Company, Most Admired Corporate Culture, and Great Place to Work, Klick is committed to fostering a high-performance, people-first culture with creativity, collaboration, innovation, and impact across everything we do.

About our Omnichannel Enablement Craft

Omnichannel Enablement brings channels, data and technology together to create consistent, coordinated, and measurable experiences across every touchpoint. The craft builds omnichannel vision and roadmaps, aligns media, platforms and analytics, and turns strategy into practical, scalable solutions that improve journey effectiveness and measurement across the ecosystem. You’ll work cross-functionally — running co-creation workshops, defining capabilities, and helping teams operationalize platforms, data and technical delivery to solve complex, real-world problems. This craft includes consulting, analytics, solution delivery and technical/platform delivery functions focused on making omnichannel work end-to-end.

Job Description

The Data Solutions Analyst Intern supports the development of data pipelines, machine learning models, and analytics workflows within live client engagements. This role is embedded in project squads and contributes hands-on to production-oriented initiatives. The position focuses on building reproducible data workflows, prototyping and evaluating models, and supporting deployment into operational environments. Success is measured by code quality, analytical rigor, delivery reliability, and the ability to translate technical outputs into actionable insights.

What You’ll Do

  • Clean, transform, and validate structured and unstructured datasets using SQL and Python to support feature engineering and analysis.
  • Prototype and evaluate machine learning or statistical models using libraries such as scikit-learn, PyTorch, or TensorFlow, documenting performance metrics and trade-offs.
  • Contribute to data pipeline development and hardening using reproducible workflows, version control, and testing practices.
  • Package and support deployment of models or analytics solutions through containerization, simple APIs, or structured hand-offs to engineering teams.
  • Document notebooks, scripts, and workflows and present technical and non-technical summaries to cross-functional stakeholders.

Qualifications

Required:

  • Graduating by April 2026 or graduated within the past two years from a program in a Master’s program in Data Science, Computer Science, Statistics, or closely related quantitative field, with coursework in machine learning and data systems.
  • Demonstrated proficiency in Python with applied use of libraries such as pandas and scikit-learn through academic or project-based work.
  • Strong SQL skills demonstrated through complex queries involving joins, aggregations, and transformations on structured datasets.
  • Applied understanding of supervised learning, evaluation metrics, and cross-validation demonstrated through coursework or model development projects.
  • Experience producing reproducible analyses using version control (e.g., Git) and communicating findings to both technical and non-technical audiences.

Desired:

  • Comfort and enthusiasm for using AI as a regular part of how work gets done.
  • Experience with cloud data platforms (e.g., BigQuery, Snowflake, AWS, GCP, Azure) or distributed processing tools such as Spark.
  • Exposure to CI/CD practices, Docker, Airflow, or simple API deployment workflows through coursework or internships.
  • Experience designing experiments or A/B tests with defined evaluation frameworks.
  • Exposure to healthcare, pharmaceutical, or omnichannel marketing data through academic projects or internships.

Additional Information

This posting is for a newly created role at Klick. The base salary for this position is CAD 60,000 per year and will be determined based on several factors such as a candidate’s work location, their unique skill set, education, and prior work experience.

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.

Top Skills

Airflow
AWS
Azure
BigQuery
Docker
GCP
Git
Python
PyTorch
Scikit-Learn
Snowflake
SQL
TensorFlow

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