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Senior Data Scientist – Fraud Detection & AI Application
Purespectrum
HyderabadHybrid2w ago
- Employment
- Full-time
- Seniority
- Senior
About the role
- Architect Real-Time Risk & Fraud Systems: Design, train, and deploy high-throughput machine learning models to detect identity spoofing, survey fraud, and bot nets. Expand these capabilities into broader cybersecurity risk scoring, threat intelligence, and vendor risk assessments.
- Process large scale transaction data: Build robust, distributed data pipelines to ingest massive transaction volumes. Perform deep exploratory data analysis (EDA) to identify complex behavioral patterns and anomalies.
- Lead Technical Groundwork & Best Practices: Take ownership of the end-to-end ML lifecycle. Drive engineering excellence by actively contributing to code reviews, system design discussions, and establishing robust data science methodologies across the team.
- Cross-Functional Prototyping & Expansion: Translate ambiguous customer and business needs into concrete ML solutions. Design and build prototypes across varied platform use cases, optimizing data quality and sample delivery. Design and interpret back tests or offline evaluations for ML and rules-based systems.
- Drive Agentic AI Innovation: Build autonomous AI agents (leveraging LLMs and RAG) to monitor external channels (e.g., scraping online forums for threat intelligence), enforce data quality, and automate operational overhead like code documentation.
- Advise & Communicate: Effectively communicate modeling choices, trust, and interpretability while delivering demos, executive presentations, and clear rollout plans.
- Education: Advanced degree (Master’s) in a quantitative STEM field (Computer Science, Statistics, Mathematics, Engineering, Physics) or equivalent professional experience solving complex analytical problems.
- Experience: 5+ years of hands-on, production-level experience applying data science to real-world challenges, ideally within a high-growth tech, cybersecurity, or product-driven startup environment.
- Advanced ML & Stats Fundamentals: Deep theoretical and practical knowledge of statistical modeling, anomaly detection, evaluation metrics, and experimentation frameworks.
- Programming Mastery: Production-level coding proficiency in Python and advanced SQL.
- Cloud & ML Frameworks: Deep expertise with traditional ML libraries (Scikit-learn, XGBoost) and modern cloud-based MLOps pipelines (AWS, GCP, Databricks, MLFlow).
- Domain Expertise: A proven track record in fraud detection, cybersecurity, threat intelligence, or risk scoring.
- Communication & Leadership: Excellent stakeholder-management skills. You are comfortable navigating diverse teams, partnering with product management, and communicating complex findings to non-technical audiences.
- GenAI & LLMs: Genuine enthusiasm and hands-on exposure to modern LLMs, modern modeling approaches, and deploying Agentic AI for business workflows.
- Intellectual Curiosity: A visible track record of your craft via GitHub profile showcasing personal ML/AI projects, open-source contributions, research publications, hackathon participation or strong rankings in Kaggle competitions (especially in fraud or anomaly detection tracks).
- We foster a modern, collaborative and inclusive culture that values flexibility, creativity, and open communication.
- Our team enjoys a competitive compensation and benefits package, including comprehensive health insurance, Provident Fund (PF), and other perks that support overall well-being.
- We offer a robust leave policy covering casual, sick, and vacation leaves, along with special leaves for key life events.
- Regular team events, celebrations, and engagement activities strengthen our sense of community and belonging.
- At PureSpectrum, you’ll find a relaxed yet high-performing workplace where you can grow professionally, build meaningful connections, and truly be yourself.
Perks & benefits
- Medical Insurance
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