Senior Data Scientist_Experimentation_Data Pipeline

Lowe’s is a FORTUNE® 100 home improvement company serving approximately 16 million customer transactions a week in the United States. With total fiscal year 2024 sales of more than $83 billion, Lowe’s operates over 1,700 home improvement stores and employs approximately 300,000 associates. Based in Mooresville, N.C., Lowe’s supports the communities it serves through programs focused on creating safe, affordable housing, improving community spaces, helping to develop the next generation of skilled trade experts and providing disaster relief to communities in need. For more information, visit Lowes.com.

Lowe’s India, the Global Capability Center of Lowe’s Companies Inc., is a hub for driving our technology, business, analytics, and shared services strategy. Based in Bengaluru with over 4,500 associates, it powers innovations across omnichannel retail, AI/ML, enterprise architecture, supply chain, and customer experience. From supporting and launching homegrown solutions to fostering innovation through its Catalyze platform, Lowe’s India plays a pivotal role in transforming home improvement retail while upholding strong commitment to social impact and sustainability. For more information, visit Lowes India

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 Senior 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:

Data Pipeline Development and Optimization:

• Design, develop, and maintain robust data pipelines to ensure efficient and accurate data flow from various sources to the data warehouse.

• Ensure the integrity and consistency of experimental data, enabling accurate analysis and reliable insights to drive decision-making and optimize business strategies.

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:

• Ph.D. or master’s 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.