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Senior Data Scientist

Stash

New York
Data

Job Score

80 pts
On-site model (+70) Data (+10)

Want to help everyday Americans invest and build wealth? Financial inequality is increasing, and too many people are getting left behind. At Stash, we’re passionate about democratizing wealth creation through education, advice, and products that help customers achieve greater financial freedom. We also believe in working smarter—leveraging AI and emerging technologies to move faster, operate more efficiently, and focus our time on solving meaningful problems for our customers.

We’re looking for a Senior Data Scientist (Technical Level 4) to join our Data team. You’ll be a strategic partner to Product, Growth, and Marketing—turning ambiguous business questions into rigorous measurement, experiments, and models that improve how we acquire, activate, retain, and advise customers.

This is not a pure reporting role. You’ll own high-impact analytical workstreams end-to-end: define the problem, choose the right method, ship trustworthy results, and influence decisions with clear recommendations. If you thrive at the intersection of statistics, product sense, and stakeholder partnership, we’d love to hear from you.

What you'll do: 

  • Own measurement for priority bets: Partner with Product and Growth on our Ideal Customer Profile, payback, attribution, subscription performance, and Financial Advice (FA) measurement—so leaders can trust the numbers behind company OKRs.
  • Design and analyze experiments: Lead A/B testing with Product and Marketing. Apply statistical rigor and translate results into ship / iterate / kill recommendations.
  • Build predictive and causal models: Develop and productionize models for churn, LTV, conversion propensity, and related outcomes. Prefer approaches that are measurable in business terms and maintainable in our stack—not science projects that never ship.
  • Deep-dive customer and funnel behavior: Analyze acquisition → activation → retention → referrals. Find drop-offs, segment opportunities, and growth levers; size impact before teams invest engineering or media spend.
  • Partner on data foundations: Specify grains, definitions, and acceptance criteria for new data mart fields and models; work with Analytics Engineering so DS work runs on governed, tested warehouse data—not one-off SQL that drifts.
  • Enable decision-making with clarity: Build durable analyses, Hex notebooks, and Looker / Mixpanel views where they create lasting leverage. Communicate findings to technical and non-technical audiences with crisp narratives and recommended actions.
  • Raise the bar for the team: Review methodology and code, and contribute to team standards for experimentation, documentation, and AI-assisted workflows (with judgment on sensitive data).

What we're looking for: 

  • Experience: 5+ years in data science or advanced analytics roles, ideally in consumer tech, fintech, or growth/product analytics. Prior Senior ownership of ambiguous, multi-quarter problems.
  • Statistical & ML craft: Strong foundation in experimental design, causal inference, and applied machine learning (classification/regression, survival/churn, uplift or propensity where relevant). You know when a simple model beats a complex one.
  • Programming: Proficiency in Python and advanced SQL against large warehouses.
  • Business partnership: Proven ability to work with PMs, designers, marketers, and engineers; connect analyses to CAC, LTV, retention, ARPU, and other commercial outcomes.
  • Product sense: Comfortable navigating incomplete instrumentation, defining metrics, and pushing for clean event/warehouse contracts when measurement depends on them.
  • Communication: Excellent written and verbal communication; can brief executives and coach peers without drowning either audience in jargon.
  • Education: Bachelor’s or Master’s in a quantitative field (CS, Statistics, Math, Economics, or related), or equivalent experience.
  • AI fluency: Hands-on use of AI coding assistants (e.g. Cursor, ChatGPT) as part of daily workflow, with strong judgment—validating outputs, following Stash guidelines for sensitive data, and owning the quality of AI-assisted work.

Gold Stars: 

  • Experience with attribution modeling, incrementality / geo or holdout tests, and marketing mix or media measurement.
  • Familiarity with dbt, dimensional modeling, and reading warehouse lineage.
  • Experience with Looker, Mixpanel, and/or Hex (or similar BI / product analytics / notebook stacks).
  • Fintech, brokerage, banking, or subscriptions experience; comfort with regulated-data hygiene.

#LI-Hybrid

Our Commitment to Diversity, Equity, and Inclusion

We proudly celebrate the unique qualities that make you you, 365 days a year, and not just because it’s the right thing to do or good for business. We embed the principles and practices of diversity, equity, and inclusion (DEI) into all that we do to prioritize people, a Stash core value, and to ensure Stashers of all backgrounds and experiences can be their authentic selves. 

We are also proud to be the first and only venture-backed fintech to join the CEO Action for Diversity & Inclusion™, and as an Equal Opportunity Employer, Stash is committed to building an inclusive environment for people of all backgrounds.

If you require any reasonable accommodations to make your application process more accessible, please reach out to recruiting@Stash.com.

Helping You Invest in Yourself 

  • Comprehensive total rewards package, comprising compensation (salary and equity) and health care benefits 
  • Complimentary subscription to Stash+ account 
  • Flexible work policy – We offer a flexible work environment that blends working from home with in-person collaboration at our NYC office to support productivity and team culture.                   
  • Flexible PTO 
  • Annual learning and development reimbursement benefit 
  • Work-from-home equipment stipends; home internet subsidy
  • Paid Parental Leave (offerings for birth giving and non-birth giving parents) Primary & Secondary
  • Enhanced health and wellness benefits through One Medical, Gympass, and Maven Health

External Recognition for Stash

  • Benzinga’s 2023 Best Brokerage for Beginners and Best Robo-Advisor Awards
  • Qorus-Accenture’s 2023 Banking Innovation Awards
  • USA Today and Statista’s 2023 Top 500 Best Financial Advisory Firms
  • Comparably's Best Company Awards: Best Places to Work, Best Company Outlook, and Best Engineering Team for Diversity, Women, Culture, and more! (2023)
  • Fintech Breakthrough Award: Best Personal Finance App (2023)
  • BuiltIn’s Best Places to Work (2022, 2021, 2020, 2019)
  • Forbes Fintech 50 (2021, 2020, 2019)
  • Best Digital Bank, Finovate Awards (2020)
  • Tearsheet Challenge Awards, Best Banking Card Product - Stock-Back® Card, 2020
  • LendIt Fintech Innovator of the Year (2020, 2019)

Salary Range: $150,000 - $180,000

The base salary range represents the reasonably anticipated low and high end of the salary range for this position. Actual salaries will vary and will be based on various factors, such as the candidate’s qualifications, skills, experience and competencies, as well as internal equity and alignment with market data for companies of our size and industry.

**No recruiters, please**

About Data

The Data field has undergone a radical transformation with the rise of Generative AI. Data professionals are fundamental for evidence-based decision-making across all industries.

Key specializations include Data Engineering, Data Science, Business Intelligence, Machine Learning Engineering, and Analytics. Tools like SQL, Python, Spark, dbt, and cloud platforms (AWS, GCP, Azure) are essential.

The data market continues with high demand and salaries among the most competitive in the technology sector, with many remote work opportunities.

Discover Other Areas

Understand the scope of work, key skills, and tools used in different career areas.

About Digital Marketing

Digital Marketing is a constantly expanding field, driven by e-commerce growth and the need for a strong digital presence. Marketing professionals master tools like Google Ads, Meta Ads, HubSpot, Google Analytics, and automation platforms.

Most sought-after specializations include Growth Marketing, Performance, SEO, Content Marketing, and Growth Hacking. The combination of creativity with data analysis is the most valued differentiator in the market.

The market offers opportunities in both agencies and technology companies, with competitive salaries and remote work possibilities.

About Traffic Analyst

The Traffic Analyst (paid media/performance specialist) is the professional responsible for creating, managing, and optimizing sponsored ad campaigns on digital platforms such as Google Ads, Meta Ads, LinkedIn Ads, and TikTok Ads. They monitor conversion metrics, analyze return on investment (ROAS), perform A/B testing on ads and landing pages, and manage the marketing budget to maximize lead generation and qualified sales.

About Automation Engineer

The Automation Engineer is the professional responsible for designing, developing, and implementing solutions that automate manual and repetitive processes in IT, infrastructure, testing, and operations. They combine programming knowledge with DevOps and SRE vision to eliminate manual tasks and increase operational efficiency.

Key skills include Infrastructure as Code (Terraform, Ansible, Pulumi), CI/CD (Jenkins, GitHub Actions, GitLab CI), test automation (Selenium, Cypress, Playwright), network automation (Netconf, SDN), RPA (UiPath, Power Automate), and scripting (Python, Bash, PowerShell). Knowledge of Kubernetes, GitOps (ArgoCD, Flux), and automation platforms is a differentiator.

Automation Engineers in technology companies are highly valued, especially those who can create automated deployment pipelines, self-healing infrastructure, and internal developer platforms (IDP). The field offers opportunities from junior automation engineer to automation architect and head of automation.

About Tech Recruiter

The Tech Recruiter is a professional specialized in recruiting technology talent, from developers to AI engineers and DevOps professionals. They combine technical knowledge with recruitment skills to evaluate and attract highly qualified candidates.

Key skills include technical screening, analysis of technical profiles (GitHub, portfolios, blogs), knowledge of software stacks and architectures, networking in tech communities and events. Proficiency with tools like LinkedIn Recruiter, Gem, Ashby, and technical assessment platforms is a differentiator.

Tech Recruiters are scarce and highly paid professionals, especially those who can map and access passive talent in competitive markets like AI, data engineering, and cloud computing.

About Ecommerce Analyst

The Ecommerce Analyst is the professional responsible for analyzing online sales data, buyer behavior, and virtual store performance to guide strategic decisions. They combine data analysis with ecommerce knowledge to optimize conversion, average order value, and return on investment.

Key skills include Google Analytics (GA4), Hotjar, conversion funnel analysis, cohort analysis, customer segmentation, pricing analysis, and ecommerce metrics (CAC, CLV, AOV, conversion rate). Knowledge of SQL, Power BI, Google Tag Manager, and platforms like Shopify and VTEX is a differentiator.

Ecommerce Analysts in technology companies are highly valued, especially those who can turn buyer behavior data into actionable insights to increase revenue and reduce cart abandonment. The field offers opportunities from junior analyst to ecommerce analytics manager.

Career Guides

Technology Career Guide

Planning, skills, interviews, and professional growth in IT, Data Science, DevOps, and Product.

Read full guide →

Design Career Guide

UX/UI, Graphic Design, Product Design. Portfolio, tools, interviews, and growth in the Design field.

Read full guide →

Marketing Career Guide

SEO, Paid Media, Growth, Content Marketing. Certifications, tools, and strategies to grow in Digital Marketing.

Read full guide →

Finance Career Guide

Financial market, investments, corporate finance, certifications, and strategies to grow in the financial field.

Read full guide →

Communication Career Guide

Journalism, PR, Corporate Communication, Content Marketing, and Multimedia Production.

Read full guide →

Administration Career Guide

Business Management, HR, Logistics, Consulting, Project Management, and Entrepreneurship.

Read full guide →

Data Career Guide

Data Science, Data Engineering, BI, Machine Learning, and AI. From training to the job market.

Read full guide →

Product Career Guide

Product Management, Product Ownership, Agile, Scrum, and OKRs. From strategy to execution.

Read full guide →

Tech & Remote Glossary

Stop getting lost in interviews and job descriptions

The job market, especially within tech and global companies, has developed its own dialect. Not understanding these acronyms can make you lose valuable opportunities or poorly negotiate your contract. To end this problem, we created the Definitive Glossary for the Remote Professional.

🏢 Work Models & Routine

Async (Asynchronous Work)
A communication model where responses don't need to be immediate. Instead of back-to-back meetings, the team relies on well-structured documents, threads, and messages. It's the gold standard for global companies spanning multiple time zones.
Sync (Synchronous Work)
The opposite of Async. It requires the team to be online and available at the same time for meetings, live chats, and real-time collaboration.
Daily / Stand-up
A quick daily meeting (usually 15 minutes) common in Agile (Scrum) methodologies. The team answers three questions: What did I do yesterday? What will I do today? Are there any blockers?
All-Hands / Town Hall
A company-wide meeting involving all employees. Usually led by the founders (C-Levels) to present results, new goals, and answer team questions.
1:1 (One-on-One)
A recurring individual meeting between a professional and their direct manager. It is used for career alignment, feedback, and problem-solving, not just for project status updates.

💰 Contracts, Benefits & Compensation

PTO (Paid Time Off)
Instead of strict, categorized leave policies, modern US companies usually offer a flexible pool of days (e.g., 20 days of PTO, or even "Unlimited PTO") that you can use for vacations, sick days, or personal matters, while receiving your regular compensation.
Equity / Stock Options
Company ownership. The startup offers you the right to buy shares at a heavily discounted strike price in the future. If the company grows, goes public, or is acquired, these shares can be highly lucrative.
Vesting (Vesting Schedule)
The rule that controls your Equity. It usually lasts 4 years. You don't get all the shares on day one; you "earn" them gradually as you stay with the company. A "1-year Cliff" means you must stay for at least one year to receive your first batch of shares.
RSUs (Restricted Stock Units)
Unlike Stock Options (where you have the right to buy the stock), RSUs are actual shares the company grants you as a bonus or part of your compensation package, following a strict Vesting schedule.
Independent Contractor (1099 / B2B)
The most common international hiring model for global talent working for US companies. You act as a service provider (business-to-business), receiving the gross salary (often six-figure compensation) without standard local payroll tax deductions at the source.

🤖 Recruitment & Hiring Process

ATS (Applicant Tracking System)
The "robot" that reads your resume. Software like Greenhouse, Ashby, and Workday are used to filter candidates by keywords before a human even looks at the document. (Pro tip: this is why your resume must be clean, semantic, and have the right keywords).
JD (Job Description)
The document that lists the responsibilities, technical requirements, and benefits of the open position.
Cultural Fit
The interview stage that evaluates if your core values, communication style, and worldview align with the company's culture. This is the ultimate test of your Soft Skills.
Onboarding
The integration process. It's the period of your first few weeks at the company, where you get your access credentials, learn about the culture, study the internal documentation, and understand how the product works.

🚀 How to use this to your advantage?

The secret isn't just knowing what these acronyms mean, but using them actively. If during an interview for a premium tech role you ask, "How does your PTO policy and Vesting schedule work?", the recruiter will immediately perceive you as a high-level professional, familiar with the global market standards.

The remote job market requires preparation. And having the right vocabulary is the first big step to securing six-figure proposals and standing out among thousands of applicants.

Expert Tip

Why the Data Era Has Never Been More Profitable

Discover how BI professionals are shaping the corporate future, driving strategic decision-making, and landing the best global remote jobs in the market.

Reading time: 5 minutes | Category: Data / BI

The Data Market Explosion

A decade ago, oil was considered the world's most valuable resource; today, that title indisputably belongs to data. However, raw data without interpretation is just noise. It is exactly at this turning point that the Business Intelligence (BI) market exploded in demand and financial valuation.

Companies of all sizes, from agile startups to global unicorns, have realized they can no longer base their decisions on guesswork. The BI professional has become the architect of financial and operational predictability. According to Gartner, in its annual reports on the Magic Quadrant for Analytics and BI, adopting business intelligence platforms is no longer a competitive advantage, but a matter of corporate survival.

The Required Profile: Way Beyond the Dashboard

The biggest mistake professionals make when trying to transition into Business Intelligence is believing the job comes down to creating pretty visual panels (Dashboards). Today's market, especially international companies paying six-figure salaries, requires a deep analytical mindset combined with solid technical skills.

Tech Recruiters are configuring their ATS systems (like Greenhouse and Ashby) to filter candidates who master the following verticals:

  • Data Modeling and ETL: The ability to Extract, Transform, and Load data from multiple sources into a Data Warehouse or Data Lake.
  • Query Languages: Advanced proficiency in SQL remains the backbone of any data operation.
  • Advanced Visualization: Tools like Microsoft Power BI (with deep knowledge in DAX), Tableau, and Looker are mandatory requirements.
  • Critical Thinking & Business Acumen: As highlighted by the Harvard Business Review, data professionals must translate technical complexity into clear answers for C-Level executives.

Compensation and the Global Job Route (US Remote)

The Business Intelligence market is perfectly adaptable to the Remote Worldwide model. Because the work essentially deals with cloud infrastructure and logical analysis, geographical barriers have been completely eliminated.

"The ability to analyze massive volumes of data and extract actionable insights is the most valued skill in the new digital economy. The global market is literally buying intelligence."

For global professionals, this represents a golden opportunity. North American and European startups are actively seeking Senior BI talent to work remotely, offering compensation in strong currencies (USD and EUR) through B2B contracts. Base salaries that easily surpass the $80,000 to $120,000+ range (six-figure compensation) are a common reality for Mid-level and Senior analysts who have fluent English and a robust analytical portfolio.

How to Stand Out in the Technical Interview

To break through the technical interview barrier for premium BI positions, candidates must prepare a problem-oriented portfolio. Instead of presenting a generic sales dashboard, showcase a documented case study. Show the data source, how the SQL was structured for cleansing, which predictive or statistical models were applied, and, most importantly, what was the financial impact (ROI) of that analysis.