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Senior Data Scientist

Zynga
Toronto, Canada
$136K-$218.9K a year (estimated)
Full-time

AVAILABLE POSITIONS Senior Data Scientist

Careers Category : Data, Analytics & User Research

Careers location : Austin, TX; Toronto, Canada

Connected Worker Type : Connected

R 112324

Zynga is a leading developer of the world’s most popular social games, played by tens of millions of people around the world each day.

To date, more than 1 billion people have played our games across Web and mobile, including FarmVille, Zynga Poker, Words With Friends, Harry Potter : Puzzles & Spells, Merge Dragons!, Empires & Puzzles, Hit it Rich! Slots, Toy and Toon Blast, and CSR Racing.

The Platform ML team is a group of full-stack data scientists charged with building core products for the measurement, optimization, and automation of marketing, publishing, and product functions across this vast portfolio.

These ML products are vital to Zynga’s success, informing all facets from operational and executive decision-making.

As a full-stack data scientist, you will use your expertise across machine learning, software engineering, and business analytics to build end-to-end solutions that scale across our broad portfolio, embody CI / CD standard processes for continuous operations / improvements, and provide prescriptive actions to some of the most exciting problems in the mobile gaming space and beyond.

You will be entrusted with key initiatives and given a fair amount of autonomy, so it is critical that you bring technical excellence, a mind for architecture, and a mature sense for timelines to this role.

Responsibilities :

  • Use our modern tech stack, AWS (Redshift & Kinesis), Databricks and PySpark, Airflow, and Tableau to develop innovative tools
  • Apply statistical methodologies to evaluate performance and account for uncertainties in major initiatives
  • Implement groundbreaking machine-learning pipeline technologies to scale and propel the marketing, publishing, and product functions
  • Providing inventive thought leadership in the architecture of our pipelines
  • Design and develop in a CI / CD environment

Required Skills and Experience :

A strong statistical background building sophisticated models that can reasonably describe actual underlying data generation processes.

Experience with Bayesian modeling preferred

  • Experience exploring and implementing innovative ML / AI methods and the ability to apply that knowledge broadly across our various data pipelines to improve efficacy and efficiency
  • Experience crafting large-scale ML pipelines using technologies such as AWS tools, Databricks, and Airflow. Proficiency in SQL and Python is needed
  • Full-stack knowledge, especially around software-engineering principles such as modularity, automated testing, and documentation
  • Strong mentorship skills
  • 4+ years of work experience in data science, machine learning or analytics roles
  • BS in Computer Science, Math, Statistics, Economics, or other quantitative field; Masters or PhD strongly preferred

What we offer you :

  • Competitive salary, bonus plan and ESPP (Employee Stock Purchase Plan)
  • 401K Company Match Contribution (US)
  • RRSP / DPSP company match contribution (Canada)
  • Health coverage, dental, disability, critical illness, EAP, and life insurance (Canada)
  • Medical, dental, vision, EAP, life insurance, and disability benefits (US)
  • Virtual mental health and neurodiversity support programs
  • Global Fitness reimbursement program
  • Global Wellbeing Program
  • Financial wellness program with unlimited access to certified financial planners
  • Discretionary Time Off policy for many employees
  • Family planning support program
  • Generous paid parental, pregnancy-related disability, caregiver, and compassionate leaves
  • Subsidized Back-up child care
  • Zynga happy hours and frequent employee events
  • Flexible working hours on many teams
  • Culture of diversity and inclusion including employee resource groups
  • Work with cool people and impact millions of daily player
  • 30+ days ago
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