Senior Data Scientist - Fraud Detection & AI Application

Senior Data Scientist Fraud Detection & AI Application Hyderabad, India Data Science Hybrid Full-time Who We Are PureSpectrum is a rapidly growing market research and insights platform that simplifies technology, allowing researchers to gather and activate consumer data without disruption. As the goto solution for highquality multisourcing and fully automated research, PureSpectrum is helping to shape the future of insights. Our Marketplace facilitates over 65 million online interviews annually, and our proprietary respondentlevel scoring systemPureScorecontinues to set the industry standard for data quality and reliability. Recognized globally for both innovation and culture, PureSpectrum has been named one of Newsweeks Global Most Loved Workplaces (20232025), included in Inc.s Best Workplaces (20242025), certified as a Great Place to Work (20222025), and featured on Built Ins Best Places to Work list (20232025). PS is rapidly becoming the leading solution for quality multisourcing and endtoend automated research solution. The Opportunity We are looking for a Data Scientist to join our Data Science & AI team in Hyderabad. In this role, you will bring your deep expertise in fraud detection and threat mitigation into the dynamic ecosystem of Market Research. We need a highly technical, handson builder who can architect realtime anomaly detection systems and isnt afraid to get into the weeds of feature engineering and distributed computing. Beyond core fraud detection, you will act as a technical leader and trusted advisor, design Agentic AI systems to automate process workflows, build core product analytics, and guide crossfunctional teams (PMs and engineering) through modeling choices. You understand that deploying ML is as much a people and business challenge as it is a technical one, and you thrive in a highvelocity, dynamic environment. Location Hyderabad, India 3 days in office requirement. What Youll Do Architect RealTime Risk & Fraud Systems: Design, train, and deploy highthroughput 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 endtoend ML lifecycle. Drive engineering excellence by actively contributing to code reviews, system design discussions, and establishing robust data science methodologies across the team. CrossFunctional 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 rulesbased 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. What You Bring (MustHaves) Education: Advanced degree (Masters) in a quantitative STEM field (Computer Science, Statistics, Mathematics, Engineering, Physics) or equivalent professional experience solving complex analytical problems. Experience: 5+ years of handson, productionlevel experience applying data science to realworld challenges, ideally within a highgrowth tech, cybersecurity, or productdriven startup environment. Advanced ML & Stats Fundamentals: Deep theoretical and practical knowledge of statistical modeling, anomaly detection, evaluation metrics, and experimentation frameworks. Programming Mastery: Productionlevel coding proficiency in Python and advanced SQL. Cloud & ML Frameworks: Deep expertise with traditional ML libraries (Scikitlearn, XGBoost) and modern cloudbased MLOps pipelines (AWS, GCP, Databricks, MLFlow). Domain Expertise: A proven track record in fraud detection, cybersecurity, threat intelligence, or risk scoring. Communication & Leadership: Excellent stakeholdermanagement skills. You are comfortable navigating diverse teams, partnering with product management, and communicating complex findings to nontechnical audiences. NicetoHaves GenAI & LLMs: Genuine enthusiasm and handson 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, opensource contributions, research publications, hackathon Senior Data