2 Statisticalml Techniques Jobs

As a member of the data engineering team at PepsiCo, you will play a crucial role in developing and overseeing data product build & operations. Your primary responsibility will be to drive a strong vision for how data engineering can proactively create a positive impact on the business. Working alongside a team of data engineers, you will build data pipelines, rest data on the PepsiCo Data Lake, and facilitate exploration and access for analytics, visualization, machine learning, and product development efforts across the company. Your contributions will directly impact the design, architecture, and implementation of PepsiCo's flagship data products in areas such as revenue management, supply chain, manufacturing, and logistics. You will collaborate closely with process owners, product owners, and business users, operating in a hybrid environment that includes in-house, on-premise data sources as well as cloud and remote systems. Your responsibilities will include active contribution to code development, managing and scaling data pipelines, building automation and monitoring frameworks for data pipeline quality and performance, implementing best practices around systems integration, security, performance, and data management, and empowering the business through increased adoption of data, data science, and business intelligence. Additionally, you will collaborate with internal clients, drive solutioning and POC discussions, and evolve the architectural capabilities of the data platform by engaging with enterprise architects and strategic partners. To excel in this role, you should have at least 6+ years of overall technology experience, including 4+ years of hands-on software development, data engineering, and systems architecture. You should also possess 4+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools, along with expertise in SQL optimization, performance tuning, and programming languages like Python, PySpark, and Scala. Experience in cloud data engineering, specifically in Azure, is essential, and familiarity with Azure cloud services is a plus. You should have experience in data modeling, data warehousing, building ETL pipelines, and working with data quality tools. Proficiency in MPP database technologies, cloud infrastructure, containerized services, version control systems, deployment & CI tools, and Azure services like Data Factory, Databricks, and Azure Machine Learning tools is desired. Additionally, experience with Statistical/ML techniques, retail or supply chain solutions, metadata management, data lineage, data glossaries, agile development, DevOps, DataOps concepts, and business intelligence tools will be advantageous. A degree in Computer Science, Math, Physics, or related technical fields is preferred for this role.,

As a member of the Platform engineering team at PepsiCo, you will be the key techno-functional expert responsible for leading and overseeing the Platforms & operations. Your role will involve driving a strong vision for how Platforms engineering can proactively create a positive impact on the business. You will be the empowered Leader of a team of Platform engineers who focus on building Platform products for platform optimization, cost optimization, and developing tools for Platform ops and Data Ops on the PepsiCo Data Lake. Your responsibilities will also include enabling exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As the Leader of the Platform engineering team, you will play a crucial role in managing the platform Governance team that builds frameworks to guardrail the platforms of large and complex data applications in public cloud environments. Your work will directly impact the design, architecture, and implementation of PepsiCo's flagship data products around revenue management, supply chain, manufacturing, and logistics. You will collaborate closely with process owners, product owners, and business users, operating in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems. Your responsibilities will include: - Actively contributing to the cost optimization of platforms and services. - Managing and scaling Azure Data Platforms to support new product launches and drive Platform Stability and Observability across data products. - Building and owning automation and monitoring frameworks that capture metrics and operational KPIs for Data Platforms for cost and performance. - Implementing best practices around systems integration, security, performance, and Platform management. - Empowering the business by creating value through increased adoption of data, data science, and business intelligence landscape. - Collaborating with internal clients (data science and product teams) to drive solutioning and POC discussions. - Evolving the architectural capabilities and maturity of the data platform by engaging with enterprise architects and strategic internal and external partners. - Developing and optimizing procedures to production Alize data science models. - Defining and managing SLAs for Platforms and processes running in production. - Supporting large-scale experimentation done by data scientists. - Prototyping new approaches and building solutions at scale. - Conducting research in state-of-the-art methodologies. - Creating documentation for learnings and knowledge transfer. - Creating and auditing reusable packages or libraries. Qualifications: - 10+ years of overall technology experience with at least 4+ years of hands-on software development, Program management, and Advanced Analytics. - 4+ years of experience with Power BI, Tableau, Data Warehousing, and Data Analytics tools. - 4+ years of experience in Platform optimization and performance tuning. - Experience in managing multiple teams and coordinating with different stakeholders to implement the vision of the team. - Fluent with Azure cloud services. Azure Certification is a plus. - Experience with integration of multi-cloud services with on-premises technologies. - Experience with data modeling, data warehousing, and building Symantec Models. - Proficient in DAX queries, Copilot, and AI Skills. - Experience building/operating highly available, distributed systems of data Visualization. - Experience with at least one MPP database technology such as Redshift, Synapse, or Snowflake. - Experience with version control systems like Github and deployment & CI tools. - Knowledge of Azure Data Factory, Azure Databricks. - Experience with Statistical/ML techniques is a plus. - Experience with building solutions in the retail or in the supply chain space is a plus. - Understanding of metadata management, data lineage, and data glossaries is a plus. - Working knowledge of agile development, including DevOps and DataOps concepts. - Familiarity with Augmented Analytics tools is Plus (such as ThoughtSpot, Tellius).,