Data Scientist_Retail Forcasting

Lowe’s Companies, Inc. (NYSE: LOW) is a FORTUNE® 50 home improvement company serving approximately 16 million customer transactions a week in the United States. With total fiscal year 2023 sales of more than $86 billion, Lowe’s operates over 1,700 home improvement stores and employs approximately 300,000 associates. Based in Bengaluru, Lowe’s India develops innovative technology products and solutions and delivers business capabilities to provide the best omnichannel experience for Lowe’s customers. Lowe’s India employs over 4,200 associates across technology, analytics, merchandising, supply chain, marketing, finance and accounting, product management and shared services. Lowe’s India actively supports the communities it serves through programs focused on skill-building, sustainability and safe homes. For more information, visit, www.lowes.co.in.

About the Team

Lowe's forecasting platform team is responsible for predicting future trends, outcomes, or events based on current and historical data. The primary goal is to generate AI/ML forecasts that help the business plan for future demand, optimize resources, reduce risk, and make data-driven decisions.

Job Summary:

The primary purpose of this role is to focus on developing and deploying advanced statistical models and machine learning techniques to accurately predict future trends, behaviours, and outcomes based on historical data. This position combines deep expertise in data science with a specialised focus on time series analysis, demand forecasting and predictive analytics to support business decision-making, optimize operations, and drive planning.

Roles & Responsibilities:

• Develop, maintain, and optimize forecasting Machine Learning (ML) models for better accuracy.

• With focus on AI/ML techniques, build and deploy state of the art predictive models for use cases like item location level demand forecast, inventory and capacity planning, network flows, labor scheduling & supply chain optimisation

• Responsible for extracting actionable insights from large and complex datasets, developing predictive models, and guiding the organization in using data to improve products, services, and operations

• Collaborate with analysts, data engineers, product managers, other data scientist & leadership to translate business requirements into actionable data science solutions.

• Championing best practices and consistently working to enhance our production pipelines to improve reliability, scalability, and efficiency in terms of both time and memory.

• Research and stay abreast of state-of-the-art machine learning technologies.

Years of Experience:

• 2-4 years' experience in Data science.

Required Minimum Qualifications:

• Bachelor's/Master's degree in engineering, Computer Science, CIS, or related field (or equivalent work experience in a related field)

Skill Set Required:

• Familiar with forecasting algorithms, such as Time Series (Arima, Prophet), ML (GLM, GBDT, XgBoost), Hierarchical model (Top Down, Bottom Up), DL (Seq2Seq, Transformer), and Ensemble methods.

• Hand-on experience (real-time) in building end-to-end ML models and pipelines.

• SQL · Python · Spark, Py Spark ·

• Big Data systems - Hadoop Ecosystem (HDFS, Hive, MapReduce) or Cloud

• MLflow, Kubeflow, GCP Vertex AI, Databricks or equivalents.

• Analytics database like Druid, Data visualization/exploration tools like Superset.

• CI\CD · GIT

Secondary Skills (desired)

• Apache Airflow, Apache Oozie, Nifi

• GCP cloud experience, Big Query

• Trino/Presto

• Domain experience on retail forecasting or any other business forecast predictions/time series forecasting.