Data Scientist / ML Engineer

Job not on LinkedIn

🕒 June 26

🗽 New York – Remote

🗽 New York – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

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THEMIS Waste Recovery Technology

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2018

🏥 Healthcare

📦 Logistics

🍽️ Food & Beverage

Healthcare • Logistics • Food & Beverage

THEMIS Waste Recovery Technology is a pioneering platform focused on democratizing governance, risk, and compliance (GRC) processes for various industries. Themis provides banks, fintechs, and vendors with advanced tools to streamline compliance collaborations, accelerate partner onboarding, and automate risk assessments. With a commitment to enhancing operational efficiency and a track record of improving productivity in financial institutions, Themis is reshaping the compliance landscape with innovative solutions tailored for the banking and fintech sectors.

📋 Description

• Frame ambiguous compliance and risk problems as well-defined data and modeling tasks • Build, evaluate, and iterate on machine learning models and LLM-powered features • Design experiments and define metrics that measure real impact on customer workflows • Apply rigorous evaluation, including accuracy, explainability, and bias considerations appropriate to a regulated domain • Build and maintain data and ML pipelines for training, inference, and monitoring • Deploy models and AI features into production and monitor their performance over time • Collaborate with engineering to integrate models into the Themis platform reliably and at scale • Explore and prepare data, build features, and ensure data quality and integrity • Translate data and model findings into clear recommendations for product and leadership • Partner with Product to identify high-value opportunities for ML and AI

🎯 Requirements

• Strong foundation in machine learning, statistics, and data science fundamentals • Proficiency in Python and common data and ML libraries (e.g., pandas, scikit-learn, PyTorch, or TensorFlow) • Experience taking models or data products from prototype to production • Experience with SQL and working with real-world, messy data • Ability to design experiments, define metrics, and evaluate models rigorously • Strong communication skills and the ability to explain technical work to non-technical stakeholders • Ability to manage ambiguity and own problems end to end

🏖️ Benefits

• Flexible working hours • Remote work options