Data Scientist

Jobzhr; New York (NY); On-site; USD 250,000 - 350,000; Full time

Benefits offered by this job

High-Impact Network

Exceptional Team Environment

Direct Visibility & Ownership

Career Acceleration

Job summary

Jobzhr in New York City is seeking a highly autonomous Data Scientist to join its core engineering group, owning data products from requirements to production deployment in a fast-moving accelerator focused on blockchain, crypto, and AI.

The role is onsite in NYC, reporting to the CTO, with end-to-end ownership of data pipelines, predictive models, and analytics infrastructure. You will collaborate with cross-functional teams to drive investment decisions and operational insights.

Qualifications

• Senior-level Data Scientist capable of driving loosely defined problems to production solutions.
• Strong Python and SQL skills with experience in BI tools.
• Experience building data pipelines and production workflows.
• Familiarity with large language models and AI tooling.
• Excellent communication and stakeholder collaboration.
• Based in New York City or willing to relocate onsite.

Responsibilities

• End-to-End Ownership: translate questions into analyses, models, tooling and production systems.
• Production Engineering: deploy Python-based data workflows for data collection and enrichment.
• Predictive Modeling & Experiments: build and evaluate models, guard against data leakage.
• Data Architecture & Reporting: write SQL queries and maintain analytics infrastructure.
• Strategic Decision Support: turn data into actionable insights for investments and ops.
• Stakeholder Collaboration: work with cross-functional teams and communicate findings.

Skills

Python

SQL

Metabase

REST APIs

Data pipelines

AI tooling

Tools

REST APIs

Git

Job description

Location

New York, United States (Office) - Must be able to work office based in NYC

On-Site | Full-time

On-Site | Full-time

Compensation

$250K - $350K

Job Overview

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.

Key Responsibilities

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

Requirements

Basic Qualifications

• Professional Expertise: 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
• Technical Proficiency: Deep expertise in Python and SQL, with comfortable fluency navigating notebooks, application code bases, REST APIs, and business intelligence platforms like Metabase
• Applied Modeling Judgment: Strong technical discernment regarding feature design, model evaluation metrics, handling missing data, mitigating leakage, and choosing simple, robust approaches when appropriate
• Data Engineering Competence: Hands-on ability to build and maintain data pipelines, integrate external APIs, debug inconsistent source datasets, and manage production workflows autonomously
• Modern AI Tooling: 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
• Communication & Agency: Outstanding written and verbal communication skills; highly entrepreneurial with exceptional agency and problem-solving drive
• Location: Must be currently based in or fully willing to relocate to New York City (onsite requirement is non-negotiable)

Preferred Qualifications

• 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

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

Interview Process

• Stage 1: Hiring Manager Interview
• Stage 2: Technical Assessment / Interview
• Stage 3: Executive Interview
• Stage 4: Final Selection Interview

Commitment to Equality and Accessibility

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