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 other technologies offered by Microsoft Azure or open-source toolsets. Your responsibilities also include automating the end-to-end cycle with Azure Pipelines. You will be part of a collaborative interdisciplinary team, responsible for delivering statistical/ML models continuously. Working closely with process owners, product owners, and business users will provide you with visibility and understanding of the criticality of your developments.**Key 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 data access and preparation for model consumption- Collaborate with ML engineers on industrialization- Communicate with business stakeholders for 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- Research state-of-the-art methodologies- Create documentation for learnings and knowledge transfer- Create reusable packages or libraries- Ensure on-time and on-budget delivery, 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 model deployments**Qualifications:**- BE/B.Tech in Computer Science, Maths,



or technical fields- 2-4 years of experience as a Data Scientist- Experience building solutions in the commercial or supply chain space- Experience working in a team to deliver production-level analytic solutions- Fluent in SQL syntax- Proficient in statistical/ML techniques for supervised and unsupervised problems- Strong knowledge of building machine learning models and Python or Pyspark development- Experience with statistical programming languages like Python, Pyspark, and SQL- Valuable applied statistical skills, including knowledge of statistical tests and distributions- Experience with Cloud (Azure), Databricks, and ADF- Familiarity with Spark, Hive, Pig- Business storytelling and communicating data insights effectively- Strong communications and organizational skills- Experience with Agile methodology- Experience in Reinforcement Learning, Simulation, Optimization, Bayesian methods, Causal inference, NLP, Responsible AI- Experience with distributed machine learning, DevOps, cloud service providers- Model deployment experience- Knowledge of ML Ops, MLFlow, Kubeflow- Exceptional analytical and problem-solving skills- Stakeholder engagement experience in BU and with Vendors- Experience building statistical models in Retail or Supply chain spaceThis job offers you an opportunity to work on cutting-edge projects in the field of Data Science and Machine Learning,



collaborating with a diverse team to deliver impactful solutions within a dynamic environment. 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 setting. You will work with tools such as DS tools, Spark, Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. Your responsibilities also include automating the end-to-end cycle with Azure Pipelines. You will be part of a collaborative interdisciplinary team, responsible for delivering statistical/ML models continuously. Working closely with process owners, product owners, and business users will provide you with visibility and understanding of the criticality of your developments.**Key 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 data access and preparation for model consumption- Collaborate with ML engineers on industrialization- Communicate with business stakeholders for 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- Research state-of-the-art methodologies- Create documentation for learnings and knowledge transfer- Create reusable packages or libraries- Ensure on-time and on-budget delivery, adhering to enterprise architecture standards- Leverage big data technologies to process data and build scaled data pipelines- Implement end-to-end ML lifecycl

📌 Associate Manager - Data Science (India)
🏢 PepsiCo
📍 India