Associate Manager Data Science

As a Data Scientist in the Data Science Team, your role involves developing Machine Learning (ML) solutions to support ML/AI projects using big analytics toolsets in a CI/CD environment. You will work with tools such as DS tools/Spark/Databricks and technologies offered by Microsoft Azure or open-source toolsets. Your responsibilities include automating the end-to-end cycle with Azure Pipelines and collaborating with a multidisciplinary team to ensure the continuous delivery of statistical/ML models. You will closely interact with process owners, product owners, and business users to gain visibility and understanding of the criticality of your developments. **Responsibilities:** - Deliver key Advanced Analytics/Data Science projects within time and budget, focusing on DevOps/MLOps and Machine Learning models - Actively contribute to code & development in projects and services - Partner with data engineers to ensure proper data access and preparation for model consumption - Collaborate with ML engineers on industrialization - Communicate with business stakeholders during service design, training, and knowledge transfer - Support large-scale experimentation and build data-driven models - Refine requirements into modeling problems - Influence product teams with data-based recommendations - Conduct research on state-of-the-art methodologies - Create documentation for learnings and knowledge transfer - Develop reusable packages or libraries - Ensure on-time and on-budget delivery while adhering to enterprise architecture standards - Leverage big data technologies to process data and build scaled data pipelines - Implement end-to-end ML lifecycle with Azure Databricks and Azure Pipelines - Automate ML models deployments **Qualifications:** - BE/B.Tech in Computer Science, Maths, technical fields - 2-4 years of experience as a Data Scientist - 2+ years building solutions in the commercial or supply chain space - 2+ years working in a team to deliver production-level analytic solutions - Fluent in git (version control), understanding of Jenkins, Docker are a plus - Fluent in SQL syntax - Experience in Statistical/ML techniques for supervised and unsupervised problems - Development experience in Python or Pyspark - Hands-on experience in building machine learning models - Strong programming skills in Python, Pyspark, and SQL - Good applied statistical skills - Experience with Cloud (Azure), Databricks, and ADF is desirable - Familiarity with Spark, Hive, Pig is an advantage - Ability to communicate data insights effectively - Strong communications and organizational skills - Experience with Agile methodology - Knowledge in Reinforcement Learning, Simulation, Optimization, Bayesian methods, Causal inference, NLP, Responsible AI, distributed machine learning - Experience in DevOps, cloud service providers, model deployment, version control systems, CI/CD tools, ML Ops, MLFlow, Kubeflow, Exploratory data Analysis - Exceptional analytical and problem-solving skills - Stakeholder engagement experience in Retail or Supply chain space is beneficial As a Data Scientist in the Data Science Team, your role involves developing Machine Learning (ML) solutions to support ML/AI projects using big analytics toolsets in a CI/CD environment. You will work with tools such as DS tools/Spark/Databricks and technologies offered by Microsoft Azure or open-source toolsets. Your responsibilities include automating the end-to-end cycle with Azure Pipelines and collaborating with a multidisciplinary team to ensure the continuous delivery of statistical/ML models. You will closely interact with process owners, product owners, and business users to gain visibility and understanding of the criticality of your developments. **Responsibilities:** - Deliver key Advanced Analytics/Data Science projects within time and budget, focusing on DevOps/MLOps and Machine Learning models - Actively contribute to code & development in projects and services - Partner with data engineers to ensure proper data access and preparation for model consumption - Collaborate with ML engineers on industrialization - Communicate with business stakeholders during service design, training, and knowledge transfer - Support large-scale experimentation and build data-driven models - Refine requirements into modeling problems - Influence product teams with data-based recommendations - Conduct research on state-of-the-art methodologies - Create documentation for learnings and knowledge transfer - Develop reusable packages or libraries - Ensure on-time and on-budget delivery while adhering to enterprise architecture standards - Leverage big data technologies to process data and build scaled data pipelines - Implement end-to-end ML lifecycle with Azure Databricks and Azure Pipelines - Automate ML models deployments **Qualifications:** - BE/B.Tech in Computer Science, Maths, technical fields - 2-4 years of experience as a Data Scientist - 2+ years building solutions in the com