Staff Product Data Scientist
MLabs
Data Scientist
Location: New York
On-site | Full-time
Compensation: Competitive
Our client is a high-performance technology development company responsible for the entire technical stack behind the world’s largest and most active digital asset launchpads. Operating at the absolute edge of crypto scale, the systems managed by this organization are defined by ultra-low latency, high throughput, and constant high-concurrency load. This is a mission-critical environment where technical precision is paramount and the impact of every deployment is immediate.
The organization is seeking an experienced, versatile Data Scientist who thrives in an intense, fast-paced setting. This role provides the autonomy to identify high-impact opportunities, design sophisticated analytical solutions, and measure their direct effect on a product used by massive global audiences. Joining this team means entering a high-density talent environment that values first-principles thinking, extreme ownership, and the ability to operate independently within a high-stakes ecosystem.
Key Responsibilities
- Experimentation & Optimization: Design, execute, and analyze rigorous A/B tests to optimize the consumer product experience and drive user engagement.
- Proactive Analysis: Independently identify hidden problems and growth opportunities through deep-dive data exploration.
- Insight Visualization: Build and maintain high-fidelity dashboards to track critical KPIs and visualize complex market and user behaviors.
- Predictive Modeling: Develop sophisticated models to understand user behavior and predict outcomes in a volatile, real-time environment.
- Cross-Functional Collaboration: Partner directly with product and engineering teams to implement data-driven solutions and ensure technical feasibility.
- Project Ownership: Drive data initiatives from initial problem identification through to solution implementation and post-deployment measurement.
- Technical Communication: Translate complex statistical findings into clear, actionable narratives for both technical and non-technical stakeholders.
- Methodological Standards: Help establish and refine the organization’s data best practices and analytical methodologies.
Work Style & Environment
- In-Person Collaboration: This role is based in-person at our client's office.
- Intensity: Candidates must be comfortable with unconventional hours and an intense, high-velocity pace where expectations are high and impact is immediate.
Interview Process
- Recruiter / HR Call: Initial screen regarding background and professional motivations.
- Hiring Manager Interview I: A deep dive into technical skills and past project ownership.
- Hiring Manager Interview II: A focused discussion on experimentation, methodology, and problem-solving.
- Final Interview: Comprehensive wrap-up focusing on strategic alignment and role expectations.
Requirements
- Professional Experience: 3+ years of Data Science experience within a startup, high-growth scale-up, or FAANG-tier environment.
- Technical Stack: Advanced proficiency in Python or R , alongside mastery of SQL (specifically within BigQuery environments).
- Experimentation Mastery: Strong experience in the end-to-end lifecycle of designing and analyzing A/B tests for high-traffic consumer products.
- Execution & Agency: Demonstrated ability to work autonomously, managing entire project lifecycles from ideation to implementation without constant oversight.
- Communication: Exceptional ability to synthesize data insights into actionable business recommendations.
Preferred Qualifications
- Domain Expertise: Direct experience with cryptocurrency, blockchain data, or fintech/consumer tech products.
- Advanced Visualization: High-level skills in data visualization tools (e.g., Omni, Looker ).
- Statistical Rigor: Advanced knowledge of causal inference and complex statistical methods.
- Data Engineering: Experience building and maintaining data pipelines using modern tools such as Dagster or dbt .
- Machine Learning: Familiarity with ML methods and their practical applications in product environments.
Benefits
- Unmatched Autonomy: Significant freedom to identify projects and see them through to completion.
- Scale Exposure: Direct exposure to data systems operating at the frontier of the crypto industry.
- High Impact: The ability to ship fast and see real-world results from your work within hours or days.
- Elite Peer Group: Opportunity to collaborate with a mission-driven group of builders who hold a high bar for excellence.
- Compensation: A competitive package consisting of a Base Salary plus Equity/Tokens .
Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.
Commitment to Equality and Accessibility:
At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing View email address on click.appcast.io.
MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd’s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting View email address on click.appcast.io.
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