Manager - Data Science

<h2 dir="ltr"><span style="font-size:1.75rem;">Subex is hiring Manager – Data Science!! </span></h2><p dir="ltr"><strong>Subex | [Bangalore., India] | Full-time</strong></p><p dir="ltr"><strong>Fight fraud with AI. Lead the team that builds it.</strong></p><p dir="ltr">At Subex, we help telecom operators stay ahead of fraud and revenue leakage. We're looking for a hands-on Data Science leader to own our AI/ML practice across fraud detection, customer intelligence, and telecom product analytics, from problem framing to production deployment.</p><p dir="ltr">This role sits at the intersection of classical machine learning, Generative AI, and business strategy. You'll lead a team of 5-10 data scientists and ML engineers while staying close to the code.</p><h4 dir="ltr">What You'll Do</h4><ul dir="ltr"> <li>Mentor and develop data scientists and ML engineers at different experience levels</li> <li>Set the data science roadmap aligned with fraud, revenue assurance, and product goals</li> <li>Partner with product, engineering, and business teams to turn ambiguous problems into ML solutions</li> <li>Build a culture of experimentation, code quality, and continuous learning</li> </ul><p dir="ltr"><strong>Build fraud and risk models</strong></p><ul dir="ltr"> <li>Oversee production-grade models for subscription fraud, SIM swap, roaming abuse, account takeover, and more, using XGBoost, Random Forests, anomaly detection, and graph-based methods</li> <li>Ensure robust monitoring, drift detection, and feedback loops</li> <li>Evaluate and integrate GenAI (LLMs, RAG, agentic workflows) for fraud investigation, alert triage, and pattern discovery</li> </ul><p dir="ltr"><strong>Drive ML and GenAI delivery</strong></p><ul dir="ltr"> <li>Guide end-to-end development of classical ML and GenAI solutions</li> <li>Champion MLOps practices: model versioning, CI/CD for ML, feature stores, and experiment tracking</li> <li>Track research and industry trends and apply them to telecom use cases</li> </ul><p dir="ltr"><strong>Champion data-driven decisions</strong></p><ul dir="ltr"> <li>Establish metrics frameworks, KPIs, and self-serve dashboards for product and operations teams</li> <li>Work with BI engineers and analysts on data quality, lineage, and governance</li> </ul><h4 dir="ltr">What You Bring</h4><p dir="ltr"><strong>Must have</strong></p><ul dir="ltr"> <li>8-12 years in data science or ML engineering, including 2-3 years in a people management or technical lead role</li> <li>Strong hands-on expertise in classical ML: supervised and unsupervised learning, feature engineering, model evaluation</li> <li>Proven experience building fraud or anomaly detection systems in production</li> <li>Working knowledge of GenAI: LLMs, prompt engineering, RAG, or fine-tuning</li> <li>Proficiency in Python (scikit-learn, XGBoost, PyTorch/TensorFlow) and SQL</li> <li>Experience with AWS, GCP, or Azure and ML infrastructure (MLflow, SageMaker, Vertex AI, or similar)</li> <li>Strong communication skills, including presenting to senior leadership</li> </ul><p dir="ltr"><strong>Good to have</strong></p><ul dir="ltr"> <li>Experience in telecom, fintech, or payments</li> <li>Graph analytics or network-based fraud modeling</li> <li>Real-time scoring and streaming (Kafka, Spark Streaming)</li> <li>LangChain, LlamaIndex, or agentic AI experience</li> <li>Master's or PhD in Computer Science, Statistics, Mathematics, or a related field</li> </ul><h4 dir="ltr">The Leader We're Looking For</h4><ul dir="ltr"> <li>Equally comfortable in a model architecture review and a business strategy meeting</li> <li>Leads by example: reviews pull requests, challenges model assumptions, and debugs pipelines when needed</li> <li>Owns outcomes and prioritizes ruthlessly in a fast-moving environment</li> <li>Influences across functions without relying on authority</li> </ul><h4 dir="ltr">How to Apply</h4><h4 dir="ltr"><span style="font-size:14px;">Send your resume to </span><strong style="font-size:14px;"><a href="mailto:hamina.dadra@subex.com">hamina.dadra@subex.com</a></strong><span style="font-size:14px;"> with the subject line </span><strong style="font-size:14px;">"Application – Manager, Data Science"</strong><span style="font-size:14px;">.</span></h4>