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Lead Data Scientist

Insight Global

Vancouver

Remote

CAD 125,000 - 150,000

Full time

Yesterday
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Job summary

A leading company in the gaming industry seeks a Lead Data Scientist to drive analytics for major mobile titles. This role combines technical expertise in machine learning with stakeholder management, offering a unique opportunity to impact game development. Candidates should have a strong background in data science and excellent communication skills.

Qualifications

  • 5+ years relevant experience or 3+ years with a Master's degree.
  • Experience with supervised/unsupervised machine learning.
  • Proficient in SQL and Python.

Responsibilities

  • Lead mobile portfolio data science efforts.
  • Implement machine learning models into production.
  • Communicate with stakeholders to gather and prioritize requirements.

Skills

Machine Learning
Data Wrangling
Statistical Modelling
SQL
Python
Communication

Education

Master's in Statistics, Mathematics, Computer Science, or related field

Tools

Docker
Kubernetes

Job description

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This range is provided by Insight Global. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

CA$45.00/hr - CA$50.00/hr

Direct message the job poster from Insight Global

Insight Global is looking for a Lead Data Scientist to join a large AAA gaming company remotely in Canada for a 6-month contract to hire opportunity. As a lead of the Mobile Porfolio in the Data and Analytics team, you will be supporting some of the largest mobile game titles in a high-profile role on a cutting-edge project to find mathematically vigorous new ways of getting games in hands. This team is fast-paced, and passion driven, and requires a Lead Data Scientist that is flexible to drive value, work in an agile environment, and who wants to make immediate impact. This role is 70% hands-on technical and 30% non-technical. Non-technical aspects include communicating with product stakeholders to acquire requirements and then prioritize and execute against them. Someone who is an excellent communicator, curious, self-driven and motivated will be a good fit. Areas of technical focus include working with supervised/unsupervised machine learning models such as classification and regression, and assisting getting models into production. Further, you will be working with data science experimental design and set up and statistical modelling on a day-to-day. Proficiency with huge data sets will be necessary prior experience. Overall, someone who has experience implementing machine learning models into products in a live environment, and preferably has seen both a successful and non-successful instance, will have transferable experience to be successful in this role.

Must Haves:

  • 5+ years relevant professional experience, or 3+ years experience and a Masters in Statistics, Mathematics, Computer Science, Machine Learning, Finance, Economics, or another quantitative field
  • Experience with supervised/unsupervised machine learning (ML) such as classification and regression models, including at least some experience getting models into production (e.g. airflow, docker, Kubernetes)
  • Experience with data science experimental design and set up (e.g., treatment vs. control, statistical power) and statistical modelling (e.g., A/B testing, parametric and non-parametric tests, ANOVA)
  • Proficiency with huge data sets, including data wrangling and feature engineering capabilities
  • Proficient in SQL
  • Proficient in Python
  • Superior communication, self-starter, thought leader, strong stakeholder management capabilities

Plusses:

  • Gaming background
  • PhD in Statistics, Mathematics, Computer Science, Machine Learning, Finance, Economics, or another quantitative field
  • Experience with neural networks and/or deep learning ML models
  • Experience with causal inference experimentation data science
Seniority level
  • Seniority level
    Mid-Senior level
Employment type
  • Employment type
    Contract
Job function
  • Job function
    Information Technology
  • Industries
    Entertainment Providers

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