Data Scientist

🔥 1 minute ago

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 10%

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Provenir

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2004

☁️ SaaS

💳 Fintech

🤖 Artificial Intelligence

SaaS • Fintech • Artificial Intelligence

Provenir is the Decision Intelligence Platform for financial services providers. It offers a low-code, cloud-native SaaS platform that consolidates data, AI models, analytics and decisioning agents into a single governed environment to support credit risk, fraud & identity, compliance, onboarding, customer management and collections. The platform provides real-time, AI-powered decisioning, a data marketplace for identity/fraud/credit data, case management, and tools for deploying, validating and optimizing models and policies across global markets. Provenir is used by banks, credit unions, fintechs, payments and telco customers and processes billions of decisions annually.

📋 Description

• Support client engagements across data science, analytics, and decisioning use cases • Work with internal teams and clients to understand business problems, data availability, analytical requirements, and expected outcomes • Build, evaluate, and explain predictive models, scorecards, decision rules, segmentation analyses, simulations, and business insights • Use Python and common data science libraries to clean, explore, transform, and analyze data • Prepare analytical outputs, client-ready insights, model performance summaries, and business recommendations • Contribute data science input to discovery, workshops, demonstrations, and delivery activities • Explain how machine learning, rules, explainability, monitoring, and decisioning apply within the Provenir platform • Communicate technical concepts to technical and non-technical audiences • Document analysis, assumptions, code, and recommendations clearly and reproducibly • Follow and contribute to best practices for code quality, documentation, version control, testing, and reusable delivery assets • Collaborate with global Data Science colleagues to share learnings and support consistent regional delivery

🎯 Requirements

• Bachelor’s degree in a STEM field plus a minimum of 3 years of experience in data science, analytics, decision science, applied machine learning, or a related field; or a master’s degree or equivalent experience in a related STEM field • Experience building, validating, or interpreting machine learning models in Python • Strong data manipulation skills, including merging, cleansing, sampling, profiling, and preparing data for analysis • Practical, hands-on experience using AI tools such as Copilot, Codex, Claude Code, or OpenCode • Ability to balance model performance, explainability, complexity, and business usability • Understanding of model evaluation concepts including AUC, precision, recall, lift, stability, and model monitoring • Ability to translate analytical outputs into clear insights and recommendations • Experience communicating directly with clients and internal stakeholders • Curious, proactive, and willing to learn new business domains, analytical methods, and platform capabilities • Organized and delivery-focused, with ability to manage multiple priorities • Experience in financial services, fintech, banking, lending, payments, insurance, telecommunications, or another data-rich industry is desirable • Exposure to client-facing work, workshops, product demonstrations, or cross-functional business discussions is desirable • Experience with MLOps, model deployment, APIs, MLflow, CI/CD, or production model governance is desirable • Familiarity with credit risk, fraud, collections, or customer management use cases is desirable • Experience preparing presentations, technical documentation, or business summaries for data science initiatives is desirable

🏖️ Benefits

• Comprehensive health and wellness plans • Paid time off and company holidays • Flexible and remote-friendly options • Maternity/paternity leave • Equal employment opportunity and inclusive workplace • Opportunities to work with enterprise customers and solve meaningful challenges • Exposure to global teams, client engagements, and commercial data science work