Data Science Analyst @ Pepsico

• 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 Machine Learning and Azure Pipelines

• Automate ML models deployments

• BE/B.Tech in Computer Science, Maths, technical fields.

• Overall 5+ years of experience working as a Data Scientist.

• 4+ years experience building solutions in the commercial or in the supply chain space.

• 4+ 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.

• 4+ years experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems.

• 4+ years experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or Pyspark development.

Skills, Abilities, Knowledge:

• 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 likeSQL

• 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, Pigis 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.