Data Scientist

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Supply Wisdom

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

🛡️ Insurance

🏥 Healthcare

💰 $11.5M Venture Round on 2022-01

Consulting • Insurance • Healthcare

Supply Wisdom is a company that provides a comprehensive, actionable platform to manage risk through continuous, real-time risk intelligence. They empower businesses to grow by offering third-party risk management solutions that include real-time alerts and proactive monitoring of essential third parties and locations. Supply Wisdom's integrative software offers over 350+ risk metrics, allowing for comprehensive intelligence and a full spectrum of potential risk identification. Their solutions enable companies to maintain oversight and make informed decisions to protect business health and growth. Additionally, Supply Wisdom employs machine-learning technology to provide verified insights that help companies enhance visibility across their supply chain and third-party relationships.

📋 Description

• Take on ambiguous, open-ended problems (e.g. "improve target coverage in this risk domain" or "reduce false positive rate for this classifier") and independently structure an approach, build it, and iterate toward a working solution. • Design, build, and maintain data pipelines and ML models that identify, detect, and quantify risk intelligence across financial, cyber, operational, ESG, and compliance domains. • Prepare, clean, and structure large and often messy datasets for modeling, exercising judgment on where automation, direct data integration, or LLM-based approaches each make the most sense. • Build and continuously refine predictive and classification models (e.g. credibility scoring, urgency/severity classification, entity resolution), evaluating performance against real outcomes and iterating based on data-driven feedback. • Engage directly with product, engineering, and occasionally customer-facing stakeholders to translate business and methodology questions (e.g. model bias, data confidence, coverage limitations) into clear technical answers and solutions. • Use Python and standard data science/ML libraries alongside strong database and querying skills to move fluidly from data prep to modeling to production. • Proactively evaluate and adopt new tools and techniques, including AI-assisted workflows, to accelerate your own delivery rather than defaulting to manual or established methods. • Document your methodology, code, and data schemas clearly enough that teammates and stakeholders can build on your work.

🎯 Requirements

• 3-5 years of experience in applied data science, machine learning, or a closely related technical role. • Strong Python skills across the data science and ML stack (pandas, NumPy, scikit-learn, TensorFlow, PyTorch or equivalent). • Solid database and data engineering fundamentals — comfortable designing schemas, writing efficient queries, and building reliable pipelines, not just consuming clean data. • Experience deploying models into production and monitoring their performance, not just building them in a notebook. • Excellent written and verbal communication skills; able to explain technical tradeoffs to non-technical stakeholders. • A track record of working with minimal supervision and following through on open items without prompting. • Degree in Computer Science, Applied Mathematics, Statistics, or a related field, or equivalent practical experience. • Nice to have: Exposure to REST API design and development (Django Rest Framework or similar).

🏖️ Benefits

• Health insurance • Professional development opportunities