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Lead Data Analyst - Remote

Remote / Online - Candidates ideally in
Boston, Suffolk County, Massachusetts, 02298, USA
Listing for: Jobcertify
Remote/Work from Home position
Listed on 2026-01-14
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Data Scientist, Data Engineer
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below

About the job Lead Data Analyst - Remote

With us, you’ll do meaningful work from Day 1. Our collaborative culture is built on three core behaviors:
We Play to Win, We Get Better Every Day & We Succeed Together. And we mean it we want you to grow and make a difference at one of the world's leading digital banking and payments companies. We value what makes you unique so that you have an opportunity to shine.

Come build your future, while being the reason millions of people find a brighter financial future with Arkestro.

What You’ll Do

Job Description
  • Gather, structure, and analyze data and provide recommendations to management.
  • Support the development of standard data analyses, reports, and dashboards.
How You’ll Do It
  • Present the results of data analyses and recommendations to management and process owners.
  • Partner with the business to identify appropriate data sources and analysis methodology.
  • Demonstrate technical knowledge of analytical tools.
Qualifications You’ll Need – The Basics
  • Masters degree in computer science, engineering, statistics, mathematics, or related field.
  • 2+ years of experience in programming with a concentration in data science, or related field.
  • In lieu of education, 4+ years Bachelors Degree in Information Technology, Engineering, Statistics, Mathematics or Related and Experience in Programming with concentration in Data Science, or related and 8+ years Programming with concentration in Data Science, or related.
Bonus Points If You Have
  • 4+ years of experience in programming with a concentration in data science, or related field.
  • Analytical tools such as SAS, H20, R, Python.
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