Data Scientist [33394]

Stealth Startup
New York, NY, United States
7 days ago
Apply on arc.dev
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Data Analysis Application Integration Architecture Information Engineering Data Infrastructure Information Leak Prevention Systems Theories Github Information Extraction Python (Programming Language) Machine Learning
+14 more
Open Source Technology Operational Databases Software Engineering SQL Databases Data Processing Freeform SQL Feature Engineering Large Language Models Model Validation Fastapi Build Tools Data Management Machine Learning Operations Data Pipelines

Job description

We’re looking for an experienced Data Scientist to join a small, high-performing engineering team. This is a highly autonomous role where you’ll own projects from problem definition through production deployment. You’ll work closely with business stakeholders to build data products, predictive models, internal tools, and AI-powered systems that drive strategic decision-making.

This position is best suited for someone who enjoys solving ambiguous problems, shipping production-quality solutions, and having direct ownership over their work.

What You’ll Do

  • Own data science initiatives end-to-end, turning loosely defined business questions into actionable analyses, models, internal tools, and production systems.
  • Build and maintain production-grade Python applications for data collection, enrichment, scoring, and AI-assisted research using both internal and external data sources.
  • Design, train, evaluate, and deploy predictive models while ensuring strong feature engineering, robust validation, and high data quality.
  • Write complex SQL queries and develop dashboards, recurring reports, ad hoc analyses, and data reconciliations.
  • Transform large, messy datasets into practical recommendations that improve investment decisions, business operations, portfolio management, and company growth.
  • Partner directly with stakeholders to identify high-impact opportunities, communicate insights clearly, and continuously improve solutions based on real-world usage.
  • Help improve internal data infrastructure, automation, and analytical capabilities across the organization., * Solve challenging technical problems that directly influence important business decisions.
  • Join a small, collaborative team where individual contributions have significant impact.
  • Build systems that combine data science, machine learning, software engineering, and modern AI technologies.
  • Work closely with experienced operators, investors, founders, and technical leaders across a broad range of industries.
  • Gain exposure to emerging technologies, high-growth companies, and real-world business challenges.
  • Enjoy meaningful ownership, rapid professional growth, and the opportunity to shape the organization’s data capabilities.

Requirements

  • Senior Data Scientist or Analytics Engineer with a demonstrated ability to independently take business problems from initial exploration to production-ready solutions.
  • Extensive experience with Python and SQL.
  • Comfortable working across notebooks, APIs, application code, and modern business intelligence platforms.
  • Strong understanding of applied machine learning, including:
  • Feature engineering
  • Model evaluation
  • Missing data handling
  • Data leakage prevention
  • Model calibration
  • Interpretability
  • Knowing when simpler solutions outperform more complex ones
  • Solid data engineering experience, including building pipelines, integrating APIs, maintaining production workflows, and troubleshooting data quality issues.
  • Excellent communication skills with the ability to explain technical findings to non-technical audiences.
  • Highly self-motivated with strong ownership and entrepreneurial instincts.
  • Comfortable leveraging modern AI tools and large language models to improve research, analysis, automation, and productivity while applying sound judgment to model outputs.
  • Must be based in New York City or willing to relocate.

Preferred Qualifications

Strong candidates may have experience with one or more of the following:

  • Building production data products or machine learning systems used by real customers or internal teams.
  • Maintaining an active GitHub profile, contributing to open-source projects, publishing technical research, or producing high-quality technical writing.
  • Applying data science to finance, venture investing, marketplaces, growth, CRM, or other operational datasets.
  • Building AI-assisted research systems, LLM evaluation frameworks, or structured information extraction pipelines.
  • Working as an early technical hire or founder at a fast-growing startup.
  • Exceptional quantitative background demonstrated through research, competitions, Olympiads, or a highly rigorous technical education., * You prefer managing projects rather than building and shipping technical solutions yourself.
  • You prioritize predictable work hours over working in a fast-moving, high-performance environment.
  • You require frequent direction or detailed task management.
  • You are unable or unwilling to work onsite in New York City.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on arc.dev
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

6:36 min

Funding open source through GitHub Accelerator and Sponsors

Stormy Peters · World Congress 2023

3:33 min

Connecting frontends via a FastAPI proxy backend layer

Saoussen Chaabnia Saoussen Chaabnia · Europe 2026 Virtual

48 sec

Exploring alternative build tools and experimental web components

Sasha Shynkevich · LIVE

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

2:40 min

Using GitHub primitives for internal documentation and corporate operations

Kyle Daigle · Coffee With Developers

Videos

See all

Related articles

See all