Machine Learning, Python, Generative AI, LLMs, Statistical Modeling

? 3–4+ years of recent and dedicated experience in Demand Forecasting (not generic time-series forecasting), ? Experience working with massive datasets (millions to billions of records), ? Expertise in building scalable forecasting solutions for:, ? Strong hands-on expertise in designing and deploying enterprise-scale forecasting models

data wrangling , Sqlalchemy, Java, Google Looker, Scala, Sql, Gcp, Flask, Databricks, FastAPI, Python, Big Query, GenAI, Classic ML, ApigeeX, SQLModel, RAG prompt engineering, Agentic AI, R, Google Cloud Storage

Java, Ruby, Automation, Python, Systems Engineering Fundamentals

linear models , causal inference , Machine Learning, MATLAB, Multivariate Analysis, Sql, Pandas, Python, Statistical Analysis, sampling methods, bidding optimization, R, Data Gathering, differential privacy, incrementality

Sql, Nlp, Gcp, Spark, Azure, Python, Computer Vision, AWS, LangChain, AI Refinery, Generative AI, Crew AI, Retrieval-Augmented Generation, AutoGen, Vector Databases, Agentic AI, Multi-Agent Systems, AI Agent Orchestration, Tool Integration, RAG, Function Calling

Apis, Sql, Python, Agent-based systems, Ai

Python, Sql, ETL processes, Financial Crime Risk, Modelling Data Process Events Objects, Analytical and statistical methods, Banking Products

Pytorch, Matlab, Tensorflow, Python, Kubernetes, Docker, R, MLflow

Pyspark, Tensorflow, Pytorch, Flask, Python, AWS, Apis, Hadoop, Sql, Gcp, Spark, Databricks, FastAPI, Azure, data science techniques, decision science approaches, Statistical Modeling, ML services, multimodal AI, big data ecosystems, Generative AI, Agentic AI frameworks, LLMs, cloud platforms, Optimization Techniques, AI ML data science pipelines