> Markdown version of [/jobs/ext/2599131-data-scientist](https://www.wearedevelopers.com/jobs/ext/2599131-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** ALLIANCE ENTERPRISES LLC - **Location:** New York, NY, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Information Engineering, Software Debugging, Github, Python (Programming Language), Raw Data, Software Requirements Analysis, SQL Databases, Delivery Pipeline, Large Language Models, Free and Open-Source Software - **Published:** August 1, 2026 - **Apply:** https://www.dice.com/job-detail/b1c08dc2-4130-4d74-8ee9-4f5588120417 ## About the Role * Senior, self-directed data scientist or analytics engineer who can take a loosely defined business problem from first query through a production-quality answer. * Deep experience with Python and SQL; comfortable working across notebooks, application code, APIs, and Metabase. * Strong applied modeling judgment: feature design, evaluation, missing data, leakage, calibration, interpretability, and knowing when a simple approach is better. * Enough data engineering depth to ship your own work: build pipelines, integrate APIs, debug bad source data, and maintain production workflows without heavy engineering support. * Clear communicator with good product judgment who can work directly with non-technical stakeholders and turn analysis into a recommendation or operating tool. * Extremely high-agency, entrepreneurial, self-driven. * Comfortable using modern AI tools and LLMs for analysis, enrichment, evaluation, and automation without treating model output as ground truth. * NYC-based or willing to relocate (non-negotiable). Examples of strong qualifications (good to have but not required) * Shipped data products or models that people actually use, with evidence of owning the path from raw data and experimentation through production and iteration. * Strong public work: a standout GitHub, useful open-source contributions, published research, technical writing, or unusually good independent analysis. * Experience applying data science to venture, finance, marketplaces, growth, CRM, or other messy operational datasets. * Experience building LLM evaluation systems, structured extraction pipelines, or AI-assisted research products. * Founder or early data hire at a fast-moving startup, especially where you operated without a dedicated data platform or large engineering team. * Clear signals of exceptional quantitative ability: strong research, competition results, Math/Physics Olympiad performance, or a top technical academic background. ## Description We're hiring a Data Scientist to join our in-house engineering team. You'll report directly to Carter (CTO) and will be responsible for owning features from the requirements definition stage to production., * Own data science and analytics end-to-end: turn ambiguous questions into analysis, models, internal tools, and production systems without waiting on a PM or a large engineering team. * Build production Python systems for data collection, enrichment, scoring, and AI-assisted research across internal and external data sources. * Develop and improve predictive models: define features, build evaluation datasets, run experiments, catch leakage and data-quality issues, and move successful work from research into reliable production releases. * Write SQL and own reporting including dashboards, recurring reports, one-off investigations, and reconciliation against source data. * Turn messy data into useful decisions for investing, portfolio support, operations, and growth. The output should be understandable and actionable, not just statistically interesting. * Work directly with stakeholders to decide what is worth building, explain findings clearly, and iterate based on how the work is actually used. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to start an AI project for a good cause and boost your career](https://www.wearedevelopers.com/magazine/15-how-to-start-an-ai-project-for-a-good-cause-and-boost-your-career) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)