Senior Data Scientist - RevX

Designation : Senior Data Scientist Office Location: Remote Position Description: We are looking for a highly skilled Mid-Senior Data Scientist to join our team and drive machine learning initiatives across our AdTech stack. The ideal candidate has strong experience in advertising optimization, user acquisition, recommendation systems, and predictive modeling, and can build scalable, production-ready ML solutions. As part of our next-generation roadmap, we are actively investing in transformer-based architectures, graph-based learning, agentic AI pipelines, and state-of-the-art ML research to build best-in-class models for ad relevance, bidding efficiency, and user intelligence. You will work closely with product, engineering, and business teams to design, build, and deploy models that directly impact campaign ROI and user engagement. Key Responsibilities Machine Learning & Modeling 1. Build and optimise models for: Advertisement recommendation / personalization User retargeting and funnel optimisation User acquisition efficiency prediction Bid prediction / CTR-CVR modeling Time-series forecasting (spend, conversions, bids, seasonality) 2. Design and experiment with transformer architectures, graph neural networks, and agentic AI workflows for next-gen AdTech solutions. 3. Develop feature pipelines, embeddings, and scalable ML architectures. Data Engineering & Production Build end-to-end ML pipelines that run reliably in production. Write clean, modular, and efficient production-grade Python code. Work with large-scale datasets using Spark, BigQuery, Hive, or similar big-data tools. Collaborate with engineering to deploy models through APIs, microservices, and batch or streaming pipelines Research & Problem Solving Conduct analytical deep-dives to uncover insights around user behaviour, campaigns, and ad inventory. Drive innovation by experimenting with transformers, GNNs, RL/agentic systems, and other frontier ML techniques. Identify opportunities for automation and optimisation using ML across the ad delivery ecosystem. Required Skills & Experience 1. Core Technical Skills 2. Python (expert-level) with strong software engineering practices. 3. SQL (advanced) for analytical queries and ETL workflows. 4. Strong experience with TensorFlow or PyTorch for model development. 5. Proficiency with Big Data ecosystems (Spark, Hadoop, BigQuery, Presto, etc.). 6. Solid grounding in: Machine learning & deep learning Time-series models Recommendation systems Statistical modeling & experimental design Transformers, attention mechanisms, or modern deep architectures (preferred) AdTech / Marketing Tech Experience (Highly preferred but not mandatory) Experience with CTR/CVR prediction, bidding algorithms, funnel optimisation, or attribution. Understanding of real-time ad delivery, event-level signals, and performance marketing data. Soft Skills Excellent problem-solving ability and strong business intuition. Ability to translate unsolved business problems into ML solutions. Ownership mindset with experience taking projects from design - production. Good to Have Experience with GNNs, transformers, or RL/agentic AI models in production. Familiarity with MLOps tools (Airflow, MLflow, Metaflow, Feature Stores). Experience with Docker, Kubernetes, or cloud ML platforms. Knowledge of streaming systems (Kafka, Fink, Spark Streaming). Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.