Sr Analyst, DACI Analytics

Job summary:
The role is part of the Data Analytics & Customer Insights team focused on Competitive Intel Analytics. The primary purpose of this role is to perform ad hoc analytics, develop and deliver analytical solutions and visualizations that would provide a holistic view of the pricing ecosystem, surface pricing opportunities, generate business-ready recommendations and measure the business impact. This would involve actively partnering with the business teams, understanding ad hoc needs and implementing rapid analytical solutions and help achieve the overall organizational goals. They would act as a true partner and a subject matter expert for analytical techniques, visualizations & BI tools within DACI and the pricing organization.

Business problem solving:
• Understand the interplay between various data sources within Lowe’s, existing analytical platforms and pricing organization needs
• Understand the business context in-depth and translate it to clear outputs
• Wear the business hat and present a point of view within a cross-functional team that ensures the final deliverable fits the business needs and can generate tangible impact
• Ability to drive and present insightful approaches to implementing new analytical approaches
• Have strong hypotheses, understand the data needed to conduct the analysis, perform the analysis, synthesize the outputs to an executive-friendly format

Technical expertise:

• Our analytical solutions require technical expertise in manipulating large volumes of data into usable format through the extensive use of SQL, R (and Python optional), to ensure that we can flexibly meet business requirements
• Further expertise is needed to develop and deploy rapid dashboards in Tableau/ Power BI/ other BI tools to meet customized needs/ analyses

Every day, sometimes every hour counts. The senior analyst would play the point person for the end quality and timely delivery of the solution. The role needs high ownership and leadership skills to rally a team from different departments, manage work dependencies from different contributors to successfully deliver the project.

• Utilizes a depth of knowledge of how to best leverage disparate data sources, relevant external data and strong domain expertise, in order to deliver on a need of the business
• Provides technical skills to analytics projects, performing more advanced project analysis and data modeling, ultimately ensuring that the final deliverable is high-quality and provides impactful insights
• Translates a business question into an analytical model that can be utilized and executed by the business; Collects, cleans, transforms, and restructures data for statistical analysis; performs statistical summaries and tests for relevant business questions
• Performs operational or customer behavior modeling and analysis in order to provide quality insights
• Creates analytic solutions by exploring innovative data and techniques; conducts exploratory data analysis and modeling
• Builds predictive and prescriptive models supporting a vast array of customer and business scenarios; performs statistical tests to enhance the predictability of models
• Maintains consistency in analytic practices by brainstorming and partnering with other areas within the broader DACI organization
• Responsible for continuously learning and sharing analytic methodology and techniques new to Lowe’s
• Develops solid hypotheses, in collaboration with business partners, on how value can be created; builds analytical models, analyses, or tests to validate/disprove these hypotheses and develops actionable recommendations for the business
• Track measures of success and develop dashboard reports that measure customer and operational metrics for one or more of Lowe’s operations, driving actionable insights
• Translates project requirements into analytical problem(s), sometimes partnering with more junior level analysts, asking the right questions and validating understanding of requirements with manager or more senior level analysts
• Contributes to or builds project plans, ensuring clear understanding of project requirements and timeline; provides guidance to more junior level analysts and communicates project timelines, scope and expectations to stakeholders
• Gathers and assimilates information/data, sometimes in partnership with more junior level analysts, using known tools, techniques, methods and models to ensure an accurate and concise output summarizing findings; discusses analysis and findings with the team before delivering to stakeholders
• Offers insight and recommendations based on the data analysis for review by more senior level analysts; discusses and incorporates ideas from more junior level analysts
• Maintains updated knowledge of evolving technology and methods that can be used for effective data analysis
• Provides input into the framework for measuring impact of the data analytics function; participates in discussions of impact with stakeholders after projects

Required qualifications:
• Bachelor’s Degree in Business, Economics, Engineering, Statistics, Data or Information Sciences, or related field AND 3 years of related experience
• Master’s Degree in Business, Economics, Engineering, Statistics, Data or Information Sciences, or related field AND 1 year of related experience
• 2 years of experience using analytic tools (e.g., Python, SQL, SAS, R, Adobe, Alteryx, Knime, Aster, Base SAS, SAS Enterprise Miner, Enterprise Guide)
• 1 year of experience working with Enterprise level databases (e.g., Hadoop, Teradata, Aster, GCP, Azure, Oracle, DB2)
• 2 years of experience using enterprise-grade data visualization tools (e.g., MicroStrategy VI, Power BI, Tableau)
• 1 year of Functional experience performing predictive analytics at a large scale enterprise

Preferred qualifications:
• Master’s Degree in Business, Engineering, Statistics, Economics or related area
• Experience with business intelligence and reporting tools (e.g., MicroStrategy, Business Objects, Cognos, TM1, Alteryx, SSIS, SQL, Svr) and Enterprise level databases (Hadoop, GCP, Azure, Oracle, Teradata, DB2)
• Experience working with big, unstructured data in a retail environment
• Experience with analytical tools like Python, Alteryx, Knime, SAS, R, etc
• Experience with visualization tools like MicroStrategy VI, Power BI, SAS-VA, Tableau, D3, R-Shiny
• Programming experience using tools such as R, Python
• Data Science experience using tools such as ML, Text mining
• Advanced knowledge of SQL
• Project management experience
• Experience in home improvement retail

Lowe’s is an equal opportunity affirmative action employer and administers all personnel practices without regard to race, color, religion, sex, age, national origin, disability, sexual orientation, gender identity or expression, marital status, veteran status, genetics or any other category protected under applicable law.