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Open nowPosted 248 days ago

Senior Data Scientist

Sourcedirect Talent18 open roles

Pay
CA$128,000 – CA$168,000 a yearly
Where
Vancouver, Canada
Work mode
On site
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Your applicationOpen nowSenior Data ScientistSourcedirect Talent · Vancouver, Canada

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The clock on this job

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11.4% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
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  2. 4.2%3 days
  3. 11.4%7 days
  4. 17.5%14 days
  5. 34.2%30 days
  6. 43.5%60 days
This job: posted 248 days ago

The posting

Senior Data Scientist

Location: Vancouver, BC Team: Data Type: Regular Full-Time (On-site)

About the Opportunity

Our client is a leading innovator in the free-to-play gaming space, known for delivering world-class player experiences through data-driven decision making and cutting-edge technology. Their collaborative, high-energy culture brings together diverse talent focused on building and operating exceptional games.

They are seeking a Senior Data Scientist with strong machine learning and statistical expertise to help transform how data informs game development and live operations.

This is a full-time, 5-days-per-week onsite role in Downtown Vancouver.

The Role

In this position, you will design, implement, and own end-to-end production machine learning systems in a cloud environment. You’ll play a key role in fostering a data-driven culture, mentoring junior team members, and partnering cross-functionally across product, design, and engineering.

This role is ideal for someone who thrives in fast-paced environments and enjoys taking ML solutions from concept to production.

Key Responsibilities

Opportunity Identification & Value Assessment

  • Identify opportunities for machine learning and automated data services
  • Evaluate potential value, risks, and costs of proposed solutions
  • Architect solutions from functional and non-functional requirements

Data Extraction & Analysis

  • Query petabyte-scale data warehouses using advanced SQL
  • Conduct exploratory data analysis, statistical testing, and feature engineering
  • Partner with data engineers on pipeline and feature store requirements
  • Review team outputs for accuracy and completeness

Machine Learning System Ownership

  • Develop and own end-to-end ML systems
  • Partner with engineers to deploy models in cloud environments (batch and real-time)
  • Support and mentor junior team members on data systems
  • Serve as a subject matter expert in key ML domains

Statistical Testing & Experimental Design

  • Design experiments and analyze results with stakeholders
  • Contribute to Bayesian A/B testing platforms
  • Translate technical findings for non-technical audiences
  • Champion statistically rigorous decision-making

Communication & Collaboration

  • Communicate project goals, progress, and outcomes cross-functionally
  • Deliver strong data visualizations and presentations
  • Partner with senior stakeholders to anticipate future needs

Required Background

  • Master’s degree in a STEM discipline (preferably thesis-based)
  • 4+ years of industry experience in data science (ideally in large-scale software/web environments)
  • Expert-level Python programming
  • Deep experience with machine learning libraries (e.g., scikit-learn, PyTorch)
  • Proven experience deploying ML models into production
  • Advanced SQL skills and strong understanding of data engineering principles
  • Strong data visualization experience (Tableau preferred)
  • Experience working in cloud environments (especially GCP and Databricks)
  • Ability to independently drive projects through ambiguity
  • Demonstrated experience mentoring junior team members
  • Strong, clear communication skills across technical and non-technical audiences

Compensation

Salary Range (Vancouver): $128,000 – $168,000 CAD

Actual compensation will be based on experience, skills, and overall fit, with room for growth over time.

Benefits & Perks Snapshot

Our client offers a comprehensive and flexible total rewards program designed to support employees’ health, wellbeing, and growth, including:

  • Day-one extended health coverage
  • Flexible benefits spending accounts
  • Retirement savings matching program
  • Monthly commuter support allowance
  • Generous PTO and paid parental leave
  • Employee & Family Assistance Program
  • Virtual healthcare access
  • Learning stipend and development programs
  • Inclusive and collaborative office environments
  • Paid volunteer day

Our client is committed to building a diverse and inclusive workforce and encourages applicants whose experience may not perfectly match every requirement to apply.

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