Data Scientist

MLabsNew York, NY
Onsite

About The Position

We are hiring on behalf of our client, an industry-leading accelerator program focusing on the intersection of blockchain, cryptocurrency, and artificial intelligence is seeking a highly autonomous and proactive Data Scientist to join its core engineering group. Having backed over 300 high-growth startups now collectively valued in the tens of billions, our client provides an exceptional launchpad for high-impact innovation. In this role, the candidate will report directly to the Chief Technology Officer and take full end-to-end ownership of data products—from defining initial requirements to deploying reliable production systems. This is an entirely onsite role based in New York City (NYC) designed for an ambitious, self-directed builder who thrives in a fast-paced, high-agency environment without requiring extensive product management or dedicated platform engineering support.

Requirements

  • Proven track record as a Senior Data Scientist or Analytics Engineer capable of driving loosely defined business problems from raw data queries to production solutions.
  • Deep expertise in Python and SQL, with comfortable fluency navigating notebooks, application code bases, REST APIs, and business intelligence platforms like Metabase.
  • Strong technical discernment regarding feature design, model evaluation metrics, handling missing data, mitigating leakage, and choosing simple, robust approaches when appropriate.
  • Hands-on ability to build and maintain data pipelines, integrate external APIs, debug inconsistent source datasets, and manage production workflows autonomously.
  • Practical experience leveraging large language models (LLMs) and advanced AI tools for data analysis, enrichment, and workflow automation, paired with a critical approach to verification.
  • Outstanding written and verbal communication skills; highly entrepreneurial with exceptional agency and problem-solving drive.
  • Must be currently based in or fully willing to relocate to New York City (onsite requirement is non-negotiable).

Nice To Haves

  • Prior experience shipping functional data products or deployed models, demonstrating full lifecycle ownership from raw experimentation through production iteration.
  • A strong public portfolio of work, such as a prominent GitHub profile, open-source contributions, technical publications, or exceptional independent analyses.
  • Experience applying data science methodology to venture capital, finance, digital marketplaces, growth analytics, or CRM operational datasets.
  • Background in developing structured extraction pipelines, LLM evaluation frameworks, or AI-assisted research tools.
  • Former founder experience or early data hire experience at a fast-growing startup operating without a dedicated data platform team.
  • Strong quantitative signals, such as advanced academic backgrounds in STEM fields (Math, Physics, Computer Science), competition accolades, or published quantitative research.

Responsibilities

  • Translate complex, ambiguous questions into rigorous analyses, predictive models, internal tooling, and production systems independently.
  • Architect and deploy Python-based production workflows for automated data collection, enrichment, entity scoring, and AI-assisted research across disparate internal and external datasets.
  • Build, evaluate, and refine predictive models by engineering features, establishing evaluation benchmarks, detecting data leakage, and transitioning research concepts into production-grade releases.
  • Write optimized SQL queries and maintain analytics infrastructure, including Metabase dashboards, recurring performance reports, ad-hoc exploratory investigations, and source data reconciliation.
  • Transform raw, complex operational data into actionable strategic insights to support investment strategies, portfolio company operations, ecosystem growth, and internal workflows.
  • Partner directly with internal cross-functional stakeholders to identify high-value problems, clearly communicate analytical findings, and continuously iterate based on operational usage.

Benefits

  • High-Impact Network: Direct exposure to top-tier founders and executives driving innovation across the AI and Web3 ecosystems.
  • Exceptional Team Environment: Work alongside a elite team of seasoned builders, technologists, and former founders with backgrounds from leading technology firms and venture ecosystems.
  • Direct Visibility & Ownership: High autonomy with minimal bureaucracy, providing a direct platform to shape organizational strategy and core capabilities.
  • Career Acceleration: Comprehensive access to an elite ecosystem offering unparalleled preparation for future entrepreneurial or executive leadership roles.
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