• Hands-on work on Data Science projects, preferably with experience in Computer Vision or NLP; • Strong command of fundamental machine learning concepts (proper data splitting, regularization, hyperparameter tuning); • Ability to define and compute performance metrics (Accuracy, Precision, Recall, F1-Score) and optimize inference time for real-time operation; • Practical experience using version control (Git) and Scrum ceremonies; • Strong knowledge of Python for data manipulation, feature extraction, and model training; • Practical knowledge of JavaScript/TypeScript for running and integrating models in the frontend; • Experience with Deep Learning frameworks (TensorFlow) and Computer Vision (integration of the MediaPipe library combined with OpenCV); • Basic system architecture knowledge and the ability to package simple applications in Docker containers for delivery to Engineering.

Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce. We are also market leaders in AI and analytics consulting in the CPG & retail industry with over 40% of our revenues coming from the sector. This is our fastest-growing sector, and we are beefing up our talent in the space. We are looking for a Senior Data Scientist with a good blend of data analytics background, practical experience in Operation research strategies and Pricing Analytics within supply chains, and strong coding capabilities to add to our team. **Key Responsibilities:** - Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming - Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG. - Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to Pricing Optimization. - Develop and implement predictive models and optimization algorithms to improve Pricing techniques. - Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions. - Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization. - Collaborate, coach, and learn with a growing team of experienced Data Scientists.

- Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming - Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG. - Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to Pricing Optimization. - Develop and implement predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource allocation across the supply chain. - Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions. - Design and execute experiments to evaluate the effectiveness of different replenishment strategies and allocation policies. - Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, and provide recommendations for continuous improvement. - Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization. - Collaborate, coach, and learn with a growing team of experienced Data Scientists.

• Build and deploy advanced predictive models for lead scoring, agent matching, price and time-on-market estimation, and conversion likelihood. • Develop production-grade RAG and GraphRAG pipelines, construct complex knowledge graphs across listings, agents, and clients, and design retrieval and ranking systems for unstructured data. • Write robust data transforms in Databricks (using SQL and PySpark) and author highly performant SQL queries across ClickHouse and PostgreSQL. • Partner closely with engineering teams to ship model and LLM outputs to production environments, frequently utilizing Inngest. • Analyze MLS data to surface actionable market trends and directly feed data-driven product features. • Design and analyze product experiments utilizing PostHog, and build comprehensive dashboards and analyses within Hex and Metabase. • Act as a strategic partner by translating ambiguous business questions into clear, actionable, and data-backed recommendations.