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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Mlabs Ltd - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $25,000.0 - $35,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Data Architecture, Information Engineering, Data Infrastructure, Information Leak Prevention, Software Debugging, Decision Support Systems, Github, Python (Programming Language), Operational Data Store, Raw Data, Blockchain, SQL Databases, Large Language Models, Model Validation, Information Technology, Free and Open-Source Software, Restful APIs - **Published:** August 3, 2026 - **Apply:** https://www.careerjet.com/jobad/us21ebb3d3bf9871e1b79e7f440380e615 ## About the Role * 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)., * 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. ## Description 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., * 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., Senior Data Scientist Position Summary Works closely with multi-disciplinary teams, including intuitional leaders and other key stakeholders in the development and implementati… + 14 hours ago, Data Scientist Position Summary The Data Scientist builds, validates, and supports the deployment of models for defined business problems. 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