Required Skills

Data Analyst

Work Authorization

  • US Citizen

  • Green Card

  • EAD (OPT/CPT/GC/H4)

  • H1B Work Permit

Preferred Employment

  • Corp-Corp

  • W2-Permanent

  • W2-Contract

  • Contract to Hire

Employment Type

  • Consulting/Contract

education qualification

  • UG :- - Not Required

  • PG :- - Not Required

Other Information

  • No of position :- ( 1 )

  • Post :- 21st Dec 2024

JOB DETAIL

  • Bachelor’s Degree in engineering, economics, physics, or a related quantitative discipline.
  • 4+ years of data analytics experience, ideally within a financial services or business analytics context.
  • Advanced SQL proficiency, including expertise with window functions, common table expressions (CTEs), performance tuning, and query optimization for large data sets.
  • Proven experience working with cross-functional data in marketing, product, finance, or operations.
  • Experience with data visualization and dashboard creation using tools such as MicroStrategy, Tableau, Power BI, Looker, QuickSight, or Excel.
  • Familiarity with statistical methods and experience using R or Python for in-depth data analysis.
  • Proactive Mindset: A natural problem-solver who identifies and investigates data inconsistencies or patterns, uncovering insights that drive business impact.
  • Strong communication skills, with the ability to explain complex analyses to both technical and non-technical stakeholders.
  • Excellent organizational and problem-solving skills, capable of transitioning from detailed analysis to high-level strategic insights.
  • Ability to influence and drive alignment through constructive dialogue without formal authority.
  • Flexibility in prioritizing tasks, selecting appropriate tools, and managing multiple projects with competing priorities.
  • Strong relationship-building skills and a desire to collaborate in a high-energy, team-oriented environment.
  • Financial Transaction Data Analysis: Experience in analyzing and mining financial transaction data for insights, with an understanding of payment technologies, payment types, credit/debit card networks, and purchase authorization/settlement processes.
  • Data Science and Modeling: Experience in building and deploying predictive models (regression, classification, clustering, time series forecasting) using Python, R, or similar tools.
  • Machine Learning: Familiarity with machine learning algorithms and their application in deriving insights from large datasets.
  • Cross-Functional Analytics Expertise: Experience working on projects across multiple business areas such as marketing, product, finance, and operations translating data into actionable business insights.

Company Information