Data Scientist / Senior Data Scientist, Analytics

Remote; San Francisco (CA); On-site; USD 130,000 - 180,000; Full time

Job summary

DoorDash is seeking experienced Data Scientists and Senior Data Scientists to guide measurement, strategy, and tactical decisions across the company. You will mentor analysts, explore large datasets, and deliver data-driven recommendations across marketing, growth, operations, and marketplace efficiency.

You will build analytics dashboards, conduct experiments, and present insights to product and business leaders.

Qualifications

• Degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain.
• 2+ years of experience in data analytics, consulting, or related role.
• Experience with funnel optimization, user segmentation, cohort analyses, time series analyses, regression models, etc.
• Proficiency in SQL queries, ETL, A/B Testing, and statistical analysis with packages like Matlab, R, SAS or Python.
• Proficiency in analytics & visualization tools (e.g. Chartio, Looker, Tableau).
• Ability to approach ambiguous problems in a structured, hypothesis-driven, data-supported way.

Responsibilities

• Use quantitative analysis and data presentation to understand what drives the business.
• Build full-cycle analytics experiments, reports, and dashboards using SQL, R, Python, or similar tools.
• Mentor junior analysts on advanced methods and solutions.
• Produce recommendations and use statistics to validate findings.
• Provide insights to help leaders understand marketplace dynamics and trends.
• Identify levers to move key metrics and propose solutions.
• Collaborate with engineering to implement, document, and monitor logging.

Skills

Quantitative analysis

Mentoring

Data storytelling

SQL

Python

Experimentation

Education

Bachelor's degree in Math/Statistics/CS or related

Tools

SQL

R

Python

Tableau/Looker

Job description

About the Team

The Analytics team is looking for experienced Data Scientists and Senior Data Scientists to guide measurement, strategy, and tactical decision-making across the company across a variety of teams and levels. Data Scientists at DoorDash work to uncover insights and turn them into relevant recommendations, driving decisions for the entire organization. Analytics is integral to all operational areas at DoorDash.

About the Role

As a Data Scientist at DoorDash, you'll use your quantitative background to mentor other scientists and dive into large datasets to guide decision-making. We solve a multitude of exciting challenges including customer acquisition, fraud and support, marketing, balancing supply and demand, new city launches, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, 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…

• 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, R, Python, or other scripting and statistical tools

• Work with and mentor junior analysts on how to use more advanced methods and solve challenges

• Produce recommendations and use statistical techniques and hypothesis testing to validate your findings

• Provide insights to help business and product leaders understand marketplace dynamics, user behaviors, and long-term trends

• Identify and measure levers to help move essential metrics and make recommendations

• Work backwards from understanding and sizing problems to ideating solutions

• Report against our goals by identifying essential metrics and building executive-facing dashboards to track progress

• Collaborate with engineering to implement, document, validate, and monitor our logging

We're excited about you because you have…

• A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain

• 2+ years of experience in data analytics, consulting, or related role

• Experience working with funnel optimization, user segmentation, cohort analyses, time series analyses, regression models, etc

• Expertise of SQL queries, ETL, A/B Testing, and statistical analysis (e.g. hypothesis testing, experimentation, regressions) with statistical packages, such as Matlab, R, SAS or Python

• Proficiency in one or more analytics & visualization tools (e.g. Chartio, Looker, Tableau)

• The insight to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way

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