Data Scientist

Stripe

Seattle, WA

Hybrid

Who this role is best for

Aimed at mid-to-senior level data scientists who can design and deploy production models while contributing to product strategy.

Best fit for

Candidates with 5+ years of data science experience and a master’s degree in a quantitative field
— “Master’s degree or foreign equivalent in Statistics, Data Analytics, Engineering or a related field, plus 5 years of related work experience”
Individuals with a track record of translating analysis into business outcomes and working across teams
— “Translate them into technical specifications and determine the feasibility of design”
Professionals skilled in building large-scale systems and mentoring engineers
— “Mentor early-career engineers to help them grow and spin up into independent engineers”

Things to consider

The role requires a significant time commitment to on-site work despite 50% telecommuting flexibility
— “40 hrs/week”
Candidates must have extensive experience in SQL and Python/R programming
— “Programming languages including Python or R”

How to stand out

Highlight experience in deploying models to production and driving business outcomes
— “drive business outcomes and deployment of the same model in production”
Showcase leadership in mentoring engineers or contributing to engineering tenets
— “Mentor early-career engineers to help them grow”
Emphasize your ability to design and analyze experiments for strategic impact
— “Designing and analyzing production experiments to drive strategic and technical outcomes”
Demonstrate your ability to work collaboratively across teams and understand system interactions
— “[REDACTED] the team’s representative during technical meetings and understand how their systems interact”

Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

Designed and built APIs and services
Translated complex data analysis into actionable business outcomes
Mentored early-career engineers

Typical background

Master’s degree in Statistics, Data Analytics, Engineering or related field5+ years of experience in data science or quantitative modeling

Skills & requirements

Required

SQLPythonRModel DevelopmentExperiment DesignTechnical Documentation

Preferred

Machine LearningData Visualization

Stack & domain

SQLPythonRModel DevelopmentModel TuningBusiness OutcomesProduct StrategyTechnical Design DocumentsAPI DesignService DesignLarge-scale System DesignMoney Movement RequestsBackwards CompatibilityForward CompatibilityCoherent PatternsExtensibilityTechnical MeetingsMentorshipCore Engineering TenetsDesign PrinciplesLeadershipCommunicationProblem SolvingDecision MakingCollaborationTeamworkProject ManagementTime ManagementAdaptabilityCritical ThinkingData ScienceQuantitative ModelingFinancial InfrastructureMoney MovementProduct DevelopmentTechnical SpecificationsQuality StandardsEngineering Tenets

About the role

Original posting from Stripe

Who we are
About Stripe
Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.
What you’ll do
Responsibilities
Scope, design, build, and maintain APIs, services, and large-scale systems that reliably and efficiently handle billions of money movement requests;
Design the next generation of Stripe products to meet the high growth needs of our company and customers;
Analyze product requirements, user needs and feedback and translate them into technical specifications and determine the feasibility of design, taking into account cost and time constraints;
Review API launches and library shapes for other teams to ensure that backwards and forward compatibility, coherent patterns, and extensibility meet our quality standards;
Act as the team’s representative during technical meetings and understand how their systems interact with the broader landscape within the company;
Mentor early-career engineers to help them grow and spin up into independent engineers; and
Construct core engineering tenets and design principles for their team’s projects.
Who you are
Minimum requirements
Master’s degree or foreign equivalent in Statistics, Data Analytics, Engineering or a related field, plus 5 years of related work experience in data science or quantitative modeling.
In the alternative, the employer will accept a Bachelor’s degree or foreign equivalent in Statistics, Data Analytics, Engineering or a related field, plus 7 years of related work experience in data science or quantitative modeling, of which at least 5 years must be post-bachelor’s progressive related work experience.
Must also have 4 years’ experience in each of the following:
SQL;
Programming languages including Python or R;
Developing models and tuning thresholds to drive business outcomes and deployment of the same model in production;
Translating complex data analysis into actionable business outcomes;
Writing or contributing to product strategy, roadmap, or technical design documents;
Must have 3 years of experience in:
Designing and analyzing production experiments to drive strategic and technical outcomes.
Salary: $193,232 - 288,000/yr
This salary range represents the base salary range for the role and any sales commissions/sales bonuses targets, if applicable, would be in addition to the base salary.
40 hrs/week
50% Telecommuting permitted
Multiple Positions Available.
Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends. WA53
#LI-DNI

Source: Stripe careers