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Associate Data Science R Jobs in Ontario (NOW HIRING)

Purpose Contributes to the overall success of the Data Engineering Team under GOCT Solution ... Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent ...

Data Scientist

Toronto, ON · Remote

CA$70K - CA$80K/yr

A degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related field * Strong skills in Python or R, plus experience with SQL * 1-2 years of hands-on experience in ...

Present outcomes, insights and r * ecommendations to senior executives with confidence and clarity ... Bachelor's or Master's degree in Statistics, Mathematics, Economics, Computer Science, Data Science ...

Principal Data Scientist

Toronto, ON · On-site

CA$129K - CA$189K/yr

This role brings data science into day-to-day product engineering, from instrumentation and ... Experience with Python or R for statistical analysis and data processing. * Hands-on experience ...

Own all stages of the data science project lifecycle, including: Develop, deploy, monitor, and ... Airflow, Redis, Flask/Django/FastAPI, SQL, R-Shiny/Dash/Streamlit. * Openness to evaluate and adopt ...

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Data Scientist, International

DoorDash Canada

Toronto, ON • On-site, Remote

Other

Posted 15 days ago


Job description

About the Team

The Analytics team is looking for Data Analysts and Data Scientists to guide measurement, strategy, and tactical decision-making using Advanced Analytics approaches, as we expand our logistics platform across the globe. Data Scientists at DoorDash work to uncover insights and turn them into actionable recommendations, helping drive decisions for the entire organisation. Analytics is very integral to all operational areas at DoorDash.

About the Role

Data Science at DoorDash involves diving deeper into our data to solve crucial business problems, ideate & run experiments to solve for insights gleaned from this deep dive and work with a cross-functional team to drive real-world operational change. It is NOT just about building Machine Learning models and putting them into production. This is a rare operational and actionable data-driven experience. 

We solve many exciting challenges from all three sides of our marketplace including customer acquisition, balancing supply and demand, fraud and support, marketing, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, are excited to build a market from 0 to 1, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you!

You're excited about this opportunity because you will...
  • Be a first-class thought partner to our product, business, finance and executive teams and help them make decisions on what's next for DoorDash
  • Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business
  • Build full-cycle analytics experiments, reports, and dashboards using SQL, Python, R, or other scripting and statistical tools
  • Produce recommendations and use statistical techniques and hypothesis testing and other experimentation techniques to validate your findings
  • Provide insights to enable our cross-functional team to understand marketplace dynamics, user behaviours, and long-term trends
  • Identify and measure levers to help move essential metrics and make recommendations
  • Possess excellent stakeholder management skills, know how to effectively collaborate well with strategy, operations, product, finance and engineering and set priorities
  • Be excited to travel to meet with business partners and the teams in each market
We're excited about you because... 
  • 3+ years of experience in data analytics, consulting, or related role
  • The insight to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way
  • The determination to initiate and lead/own strategic projects to completion with a cross-functional team
  • Experience working with experimentation techniques (A/B testing, Causal Inference) and interpreting hypothesis testing
  • Proficiency in at least one programming language (Python, R,...)
  • Expertise with SQL queries, ETLs, etc... 
  • Proficiency in one or more analytics & visualization tools
  • Experience building and training statistical and machine learning models (classifiers, regression models...)

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