The Finance Capabilities Data Analytics & Automation (DAA) team manages key data
assets that enables exceptional experiences and impactful decisions for the Target
finance organization and its large vendor community.
The team leverages key data in Finance (Accounts Payables-AP & Asset lifecycle
management-ALM primarily), Supply Chain (Receiving & Transportation) and Merch
(Vendors & Purchasing); designs and implements changes to the underlying data
assets to generate powerful insights for domestic & import payables, receiving,
deductions, freight, fixed assets & properties to support key financial metrics. This
capability allows for creative thinking, leadership opportunities and innovation to
propagate data-based decision making.
Position Overview
As a Sr Data Analyst (AP & ALM DAA) your responsibilities* will be:Closely collaborate with Finance Operations & Accounting, Assets Life cycle management business teams to identify opportunities of leveraging data, bridge gaps, and advance business capabilitiesPartner with multiple finance & upstream product, Data Sciences & Engineering,Target Tech to determine the best approach to gather, model, manipulate, analyze, and present dataWork with the team to build and maintain large & complex datasets, automated pipelines & visualizations.Analyze large datasets and apply mix of mathematical & statistical techniques for deriving insights to enable key business strategies, initiatives, and decisionsProduce clean, efficient code backed with solid documentation - based onspecifications & best practices.Taking complete ownership and accountability of the work assigned and liaisonbetween various stakeholders and team membersContribute towards data, technical, agile, and business contextual learnings forthe team, partners, and broader organization.Skills & Experiences:Analytical skills to breakdown complex problems, identify root causes, anddevelop sustainable solutionsInfluencing cross-functional teams and partnering effectively with stakeholdersat various organizational levels Developing hypotheses and producing actionable insights using advancedstatistical & mathematical techniques and tools.Proficiency in finding, manipulating, and presenting data in meaningful waystailored to varied customer preferences.Ability to communicate results of complex analytic findings to both technic/non-technical audiences and business leaders.Proven contribution in architecting large data solutions and Implementations.Implementing design architectures and building next generation analyticsStrong desire to continuously upskill and stay current with emerging industrytrends & technologies through formal training, peer training groups, and self directed educationUnderstanding of Target’s retail, analytical, and IT architecture and platformsSelf-driven and results oriented. Willing to stretch to meet tight timelines.Job duties may change at any time due to business needs.
 Qualifications: Bachelor’s/MS/M.Tech/MCA - Mathematics, Statistics, Computer Science, orother related fieldsOverall 7+ years, with minimum 5 years of data ecosystem experience.Deep Big data experience in Hadoop ecosystem and its components with advanced proficiency in programming in Hadoop/Hive, Python, SQL, Excel.Experience in developing robust and scalable data pipelines that integrates various data sources, and other platforms and supports diverse data processing needs.Proven hands-on experience with Domo, Tableau & other Visualization tools (incl homegrown platforms) Git source code management Experience in developing, monitoring, and maintaining Bots (incl homegrown platforms) using technologies such as Python, JavaScript. Strong problem solving, and ability to navigate through ambiguityExperience working in an agile environment (stories, backlog refinement, sprints,etc.).Excellent attention to detail and timelines. Strong sense of ownershipStrong team player with ability to collaborate effectively across geographies/time zones.Excellent written and verbal communication skills
 Desired:Strong addon - business contextual experience in retail and finance, including operations, KPIs, metrics and controls.Conceptual knowledge of mathematical and statistical techniques for use in data analysis and modelingFamiliarity with programmatic use of GenAI/LLMs and related ecosystem