Lead Data Scientist- AB Testing

About Lowes

Lowes 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, Lowes operates over 1,700 home improvement stores and employs approximately 300,000 associates. Based in Bengaluru, Lowes India develops innovative technology products and solutions and delivers business capabilities to provide the best omnichannel experience for Lowes 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,

About the Team

The Experimentation Team at Lowe's drives end-to-end A/B testing, ensuring data-backed decisions before full rollouts. This progressive and rapidly growing team is focused on building scalable solutions that enhance decision-making and drive top and bottom-line business value along with creating great customer experiences.

Job Summary:

We are seeking an inspiring, technically savvy, data scientist who is passionate about building a best-in-class experimentation platform/program to support our rapidly growing suite of eCommerce products.

As a Lead Data Scientist, you will be a key player in driving data-driven decision-making across the organization, collaborating closely with engineering, product, marketing, and other cross-functional teams to deliver insights and products that shape the future of our business. You will also mentor junior data scientists and help to foster a culture of experimentation throughout the organization.

Roles & Responsibilities:

Core Responsibilities:

Experimentation Design & Analysis:

• Support the design and execution of A/B tests, multivariate experiments, and randomized controlled trials (RCTs) to assess the impact of product changes, marketing campaigns, and customer experiences.
• Develop and implement robust methodologies to measure the effectiveness of business initiatives (e.g., website features, promotions, UI changes, etc.) using experimentation frameworks.
• Own the end-to-end experimentation pipeline, including hypothesis generation, experimental design, implementation, monitoring, and post-experiment analysis.
• Identify and mitigate biases in experiment design and results, ensuring statistical rigor and reliability.

Advanced Statistical Analysis & Modelling:

• Conduct advanced statistical analysis (e.g., causal inference, Bayesian analysis, regression modelling) to derive actionable insights from experimentation results.
• Develop and refine models to predict customer behavior and optimize conversion rates, retention, and other key business metrics.
• Analyze large-scale datasets and design efficient algorithms to support decision-making in areas like pricing, product recommendations, and personalization.

Continuous Improvement & Innovation:

• Stay current with the latest advancements in data science, statistics, and experimentation methodologies.
• Propose innovative approaches to enhance the experimentation framework, such as new experimental designs, alternative modelling techniques, or improved metrics.
• Lead or participate in research to explore new ways of measuring and optimizing the customer journey in a retail/e-commerce setting.

Years of Experience:

• 5+ years of professional experience in data science, with at least 2 years focused on experimentation, A/B testing, and causal inference in a retail or e-commerce environment.
• Proven track record of designing and analyzing large-scale A/B tests and experiments with demonstrable business impact.
• Strong experience with statistical analysis and modelling techniques, including hypothesis testing, regression analysis, and Bayesian statistics

Education Qualification & Certifications (optional)

Required Minimum Qualifications:

• Bachelors/Masters/Ph.D. degree in data science, Statistics, Mathematics, Computer Science, Economics, or a related field.

Skill Set Required

• Advanced knowledge of statistical methodologies for experiment design, analysis, and causal inference.
• Expertise in analytics/data software/tools such as Python, R, SQL, and experience with machine learning frameworks (e.g., TensorFlow, scikit-learn).
• Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders and executive leadership.
• Solid understanding of e-commerce and retail metrics (e.g., conversion rate, customer lifetime value, churn, etc.) and how they relate to experimentation.

Secondary Skills (desired)

• Experience with large-scale e-commerce platforms and digital product development.
• Familiarity with the advanced causal and inferential analytics
• Experience with advanced techniques in machine learning or AI that complement experimentation (e.g., recommender systems, predictive modelling).
• Familiarity with cloud-based platforms (e.g., AWS, Google Cloud, Azure).
• Experience working in an agile environment and collaborating with cross-functional teams in a fast-paced business setting.