Jun 2024 – Aug 2025 · 1 yr 2 mos · Toronto, Ontario, Canada · Hybrid

• I am leading the Enterprise Reporting initiative within the Data Office to create prescriptive reporting for the Executive Leadership, across all business units within Walmart Canada. I work closely with the Corporate Leadership Team to develop and automate reporting of critical KPIs and generate actionable insights using advanced statistical techniques. My work involves stakeholder management, requirements gathering, data discovery, managing Data Engineers and Visualization Experts, and leading the end-to-end delivery of enterprise reporting.

Sep 2023 – May 2024 · 8 mos · Toronto, Ontario, Canada · Hybrid

• I enable data-driven decision making in the Format Development Org at Walmart. I work closely with Facilities Management, Format Implementation, Fixtures, Construction, Store Design, Templates, and Store Layout teams to create an enjoyable shopping experience for Walmart's customers while leveraging our EDLP (Every Day Low Price) and EDLC (Every Day Low Cost) principles to guide my work.

May 2022 – Jan 2023 · 8 mos

• I built data solutions for Ocrolus' clients and support various internal teams at Ocrolus in measuring the impact of their work, identify opportunities to improve processes, understand the health of Ocrolus' products, and acquire new customers.

Jun 2021 – Apr 2022 · 10 mos

• I support various teams at Ocrolus in measuring the impact of their work, identify opportunities to improve processes, understand the health of Ocrolus' products, and acquire new customers.

May 2022 – Aug 2023 · 1 yr 3 mos · Toronto, Ontario, Canada

• I help business leaders take faster, more reliable, data driven decisions.
• Using my expertise with technologies such as SQL, Python, Tableau, Google Cloud Platform, Google BigQuery, AWS, Snowflake, etc along with my ability to think analytically while keeping an eye on the big picture, I help solve mission critical problems and create value for my clients and stakeholders.

Jul 2017 – Jun 2020 · 2 yrs 11 mos · Atlanta, Georgia

• I analyzed customer, demographic, transaction and product data to help various teams at The Home Depot better understand their customers and target the right people with relevant ads through appropriate marketing channels.

Jan 2017 – May 2017 · 4 mos · Greater Minneapolis-St. Paul Area

• Assisted a leading global management consulting firm to analyze and demystify the Bitcoin Blockchain data and in turn build a toolbox of reusable micro-services to identify illegal activities in the pseudonymous network.
• My responsibilities included all aspects of data sciences i.e. data engineering, data mining, model creation and testing, insight generation, storyboarding and communication of recommendations to the leadership of the client organization.

Feb 2016 – May 2016 · 3 mos

• As a Decision Scientist at Mu Sigma, I assisted a leading home improvement retailer take data driven decisions and solve their critical business problems.
• Throughout the 2+ year association with the retailer, I have assumed multiple roles and responsibilities including leading 2 teams in the Financial Planning and Analysis subgroup, building and maintaining client relationships, and contributing towards the development of the analytics ecosystem at Mu Sigma. Highlights include:
• Leading a 5-person team to develop a Tableau Dashboard that allows the client to improve merchandising decision making by identifying SKUs (Stock Keeping Units) that are performing exceptionally bad and exceptionally good as compared to their category. The dashboard also provided insight into the factors affecting the performance of these SKUs.
• Driving engagement-wide initiatives to improve the quality of deliverables and cultivate a sense of ownership towards the deliverables being sent out to the client
• Mentoring a batch of 20 new recruits on structured problem solving, storyboarding and SAS
• Other projects include:
• Conducting product line reviews for vendor management, analyzing performance of substitute SKUs and cannibalization caused by them and other analyses on ad-hoc basis.
• Technologies Used:
• SAS, SQL and Tableau

Feb 2014 – Feb 2016 · 2 yrs

• As a Trainee Decision Scientist at Mu Sigma, I assisted a leading home improvement retailer take data driven decisions in order to solve their critical business problem in the Pricing and Financial Planning and Analysis domains.
• Some of my projects include:
• Analyzing A/B testing environments to identify the optimal discount structure for returned SKUs
• Identifying transactions where excessive discounts are being offered by the store managers
• Analyzing cost of goods sold, return to vendors, markdowns and shrink in inventory to identify problematic SKUs, vendors and stores
• Analyzing cost and retail changes of SKUs and their impact on gross margin
• Recommending vendor switching to save costs
• Technologies Used:
• SAS, SQL and Tableau