Job
Description
As a Data Science professional, you will be responsible for developing Machine Learning (ML) and Artificial Intelligence (AI) projects using big analytics toolsets in a CI/CD environment. Your role will involve collaborating with a diverse team to deliver statistical/ML models, focusing on DevOps/MLOps and Machine Learning models. Key Responsibilities: - Deliver key Advanced Analytics/Data Science projects within time and budget, particularly focusing on DevOps/MLOps and Machine Learning models - Collaborate with data engineers and ML engineers to understand data and models, leveraging various advanced analytics capabilities - Ensure timely and budget-compliant delivery that meets project requirements and adheres to enterprise architecture standards - Utilize big data technologies to process data and build scaled data pipelines (from batch to real time) - Automate the end-to-end ML lifecycle using Azure Machine Learning and Azure Pipelines - Set up cloud alerts, monitors, dashboards, and logging, as well as troubleshoot machine learning infrastructure - Automate ML models deployments Qualifications: - 5+ years of overall experience, with 4+ years of hands-on work experience in Data Science/Machine Learning - Minimum 4+ years of SQL experience - Minimum 2+ years of Python and Pyspark experience - Experience in DevOps and at least 2 years in Machine Learning (ML), with hands-on experience in one or more cloud service providers like AWS, GCP, or Azure - BE/B.Tech in Computer Science, Maths, or technical fields - Stakeholder engagement experience with Business Units and Vendors Required Skills and Knowledge: - Hands-on experience and strong knowledge in building supervised and unsupervised machine learning models, with a plus for Time series/Demand Forecast models - Proficiency in statistical programming languages like Python, Pyspark, and database query languages - Applied statistical skills, including knowledge of statistical tests, distributions, regression, and maximum likelihood estimators - Experience in Cloud (Azure) technologies like Databricks and ADF, familiarity with Spark, Hive, Pig, and model deployment - Knowledge of version control systems like GitHub, CI/CD tools, ML Ops, and deploying ML models - Exceptional analytical and problem-solving skills, with experience in Exploratory Data Analysis - Ability to work with virtual teams, collaborate with technical resources, strong communication skills, and the ability to work independently with business partners - Experience with agile methodologies, negotiation, decision-making, and managing globally distributed teams The role is based in India and does not involve relocation to other PepsiCo offices outside India in the future. As a Data Science professional, you will be responsible for developing Machine Learning (ML) and Artificial Intelligence (AI) projects using big analytics toolsets in a CI/CD environment. Your role will involve collaborating with a diverse team to deliver statistical/ML models, focusing on DevOps/MLOps and Machine Learning models. Key Responsibilities: - Deliver key Advanced Analytics/Data Science projects within time and budget, particularly focusing on DevOps/MLOps and Machine Learning models - Collaborate with data engineers and ML engineers to understand data and models, leveraging various advanced analytics capabilities - Ensure timely and budget-compliant delivery that meets project requirements and adheres to enterprise architecture standards - Utilize big data technologies to process data and build scaled data pipelines (from batch to real time) - Automate the end-to-end ML lifecycle using Azure Machine Learning and Azure Pipelines - Set up cloud alerts, monitors, dashboards, and logging, as well as troubleshoot machine learning infrastructure - Automate ML models deployments Qualifications: - 5+ years of overall experience, with 4+ years of hands-on work experience in Data Science/Machine Learning - Minimum 4+ years of SQL experience - Minimum 2+ years of Python and Pyspark experience - Experience in DevOps and at least 2 years in Machine Learning (ML), with hands-on experience in one or more cloud service providers like AWS, GCP, or Azure - BE/B.Tech in Computer Science, Maths, or technical fields - Stakeholder engagement experience with Business Units and Vendors Required Skills and Knowledge: - Hands-on experience and strong knowledge in building supervised and unsupervised machine learning models, with a plus for Time series/Demand Forecast models - Proficiency in statistical programming languages like Python, Pyspark, and database query languages - Applied statistical skills, including knowledge of statistical tests, distributions, regression, and maximum likelihood estimators - Experience in Cloud (Azure) technologies like Databricks and ADF, familiarity with Spark, Hive, Pig, and model deployment - Knowledge of version control systems like GitHub, CI/CD tools, ML Ops, and deploying ML models - Exceptional
