Data Scientist - AI/ML & Programmatic Optimization

About iioniion is the leading advertising and monetization platform, reaching brands’ ideal customers across all gaming environments. Our purpose is to elevate the gaming industry by optimizing brand investments through a unified platform that empowers seamless advertising across the entire gaming ecosystem. We are ambitious trailblazers, aiming to be an indispensable element in brands' media strategy. We are a growing team of 60+ people, working primarily remote, being headquartered in Australia, consisting of teams working across APAC and Europe. Role OverviewWe’re looking for a Data Scientist (2-4 yrs experience) who is passionate about building production-grade machine learning systems and data pipelines that power advanced optimization, recommendation, and automation across programmatic and marketplace products. You will work closely with Product, Engineering, and Operations to design, build, test, and deploy models, research new algorithms, and operationalize ML solutions that improve yield optimization, bidding performance, and campaign efficiency. In this role, you will work closely with and be mentored by the VP of Technology and AI, providing a strong opportunity to develop into a specialist Data Scientist within the AdTech domain, gaining deep exposure to real-world programmatic, marketplace, and optimization problems. Role Responsibilities: AI-Driven Optimization & Algorithms • Develop and implement machine learning models for marketplace yield optimization and bid/margin optimization. • Build intelligent targeting recommendation systems that analyze user behavior and campaign data to suggest optimal audience segments, bid strategies, or placement opportunities - helping improve relevance, engagement, and performance. • Design auto-optimization frameworks for programmatic campaigns using AI/ML (including reinforcement learning or advanced supervised approaches). Model Development to Production • Write production-quality Python code and build end-to-end ML pipelines (from data ingestion and feature engineering to training, evaluation, and deployment). • Work with data engineers and infrastructure teams to operationalize models for real-time or batch serving. • Ensure proper logging, monitoring, testing, and versioning of models in production. Exploratory Analysis & Insights • Conduct exploratory data analysis on large historical and real-time campaign and marketplace data to identify patterns, correlations, and business opportunities. • Validate assumptions with data, design experiments (A/B or controlled studies), and generate actionable insights for product and operations teams. Cross-Functional Collaboration • Partner with Product and Engineering to translate business problems into ML problem statements and solution designs. • Communicate findings, model behavior, and performance implications clearly to technical and non-technical stakeholders. Performance Evaluation & Reporting • Define success metrics for models and optimization workflows; evaluate model performance rigorously and identify areas for improvement. • Generate reports and dashboards to surface key trends and model impact to internal teams. Role Requirements: Technical Skills & Experience • 2-4 years of professional experience in data science, applied machine learning, analytics, or related fields. • Strong programming skills in Python - capable of building reliable, maintainable, production-level code. • Solid experience with SQL for large-scale data querying and transformation. • Hands-on experience with machine learning libraries and frameworks (scikit-learn, TensorFlow, PyTorch, XGBoost, etc.). • Experience in feature engineering, model training, evaluation, and deployment in production environments. Machine Learning & Analytics • Practical understanding of regression, classification, clustering, ranking, recommendation systems, or optimization algorithms. • Experience with time-series models, reinforcement learning, or optimization frameworks is a strong advantage given the campaign and bid optimization focus. • Ability to conduct statistical analysis, hypothesis testing, and extract meaningful insights from complex datasets. Business Impact & Communication • Comfortable translating analytics results and model behavior into business insights that drive decisions. • Clear, effective communicator capable of explaining complex analysis and model details to stakeholders with varying technical backgrounds. Collaboration & Mindset • Strong collaborator who thrives in cross-functional environments involving product, engineering, and operations. • Data-driven, curious, and proactive - ready to explore new methods, push boundaries, and iterate rapidly on solutions. Preferred (Nice-to-Have) • Experience with real-time data platforms (e.g., Kafka, Spark Streaming) and cloud services (AWS). • Background in AdTech, programmatic auctions, DSP/SSP data analytics, or marketplace yield modeling. • Familiarity with MLOps tools for ML deployment and monitoring (Airflow, Kubeflow, MLflow, etc.). • This is a fully remote job opportunity. With a preference for candidates based in either New Delhi, Gurgaon, Mumbai, Hyderabad, Bangalore.