Data Scientist

PepsiCo Data Analytics & AI Overview : With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise.

The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AI Products. And will support “pre-engagement” activities as requested and validated by the prioritization framework of DA&AI.

Data Scientist-Gurugram and Hyderabad

The role will work 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 Machine Learning Services and Pipelines.

Responsibilities

Delivery of key Advanced Analytics / Data Science projects within time and budget, particularly around DevOps / MLOps and Machine Learning models in scope

Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities

Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards

Use big data technologies to help process data and build scaled data pipelines (batch to real time)

Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure / AWS / GCP Pipelines.

Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure

Automate ML models deployments

Qualifications

Minimum 3years of hands-on work experience in data science / Machine learning

Minimum 3year of SQL experience

Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers.

BE / BS in Computer Science, Math, Physics, or other technical fields.

Data Science – Hands on experience and strong knowledge of building machine learning models – supervised and unsupervised models

Programming Skills – Hands-on experience in statistical programming languages like Python and database query languages like SQL

Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators

Any Cloud – Experience in Databricks and ADF is desirable

Familiarity with Spark, Hive, Pig is an added advantage

Model deployment experience will be 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 required

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