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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Deputy Manager - Data Science - **Company:** PepsiCo, Inc. - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Computer Programming, Continuous Delivery, Continuous Integration, Data Security, Database Queries, DevOps, Github, Apache Hive, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Open Source Technology, Cloud Services, Standard Sql, Service Design, SQL Databases, Reinforcement Learning, Data Processing, Google Cloud, Apache Spark, Git, Pyspark, Kubernetes, Information Technology, Statistics Packages, Data Analytics, Machine Learning Operations, Software Version Control, Data Pipelines, Atlassian Bamboo, Docker, Jenkins, Databricks - **Published:** July 14, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/p4j7jglq6a ## About the Role * BE/B.Tech in Computer Science, Maths, technical fields. * Overall 2-4 years of experience working as a Data Scientist. * 2+ years' experience building solutions in the commercial or in the 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 syntaxis. * 2+ years' experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems. * 2+ years' experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or Pyspark development. * Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models. Knowledge of Time series/Demand Forecast models is a plus * Programming Skills - Hands-on experience in statistical programming languages like Python, Pyspark and database query languages like SQL * Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators * Cloud (Azure) - Experience in Databricks and ADF is desirable * Familiarity with Spark, Hive, Pig is an added advantage * Business storytelling and communicating data insights in business consumable format. Fluent in one Visualization tool. * Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities * Experience with Agile methodology for team work and analytics 'product' creation. * Experience in Reinforcement Learning is a plus. * Experience in Simulation and Optimization problems in any space is a plus. * Experience with Bayesian methods is a plus. * Experience with Causal inference is a plus. * Experience with NLP is a plus. * Experience with Responsible AI is a plus. * Experience with distributed machine learning is a plus * Experience in DevOps, hands-on experience with one or more cloud service providers AWS, GCP, Azure(preferred) * Model deployment experience is a plus * Experience with version control systems like GitHub and CI/CD tools * Experience in Exploratory data Analysis * Knowledge of ML Ops / DevOps and deploying ML models is preferred * Experience using MLFlow, Kubeflow etc. will be preferred * Experience executing and contributing to ML OPS automation infrastructure is good to have * Exceptional analytical and problem-solving skills * Stakeholder engagement-BU, Vendors. * Experience building statistical models in the Retail or Supply chain space is a plus ## Description Data Science Team works in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Azure Pipelines. You will be part of a collaborative interdisciplinary team around data, where you will be responsible of our continuous delivery of statistical/ML models. You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments. Responsibilities * Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope * Active contributor to code & development in projects and services * Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption. * Partner with ML engineers working on industrialization. * Communicate with business stakeholders in the process of service design, training and knowledge transfer. * Support large-scale experimentation and build data-driven models. * Refine requirements into modelling problems. * Influence product teams through data-based recommendations. * Research in state-of-the-art methodologies. * Create documentation for learnings and knowledge transfer. * Create reusable packages or libraries. * Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards * Leverage big data technologies to help process data and build scaled data pipelines (batch to real time) * Implement end-to-end ML lifecycle with Azure Databricks and Azure Pipelines * Automate ML models deployments ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)