

VySystems
Business Analyst or Data Analyst
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist in NYC or Toronto, with a long-term contract and a pay rate of "X". Requires 5-8 years of analytics experience, strong SQL skills, and familiarity with financial data. Preferred skills include Snowflake and BI tools.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
December 18, 2025
π - Duration
Unknown
-
ποΈ - Location
Unknown
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
New York, United States
-
π§ - Skills detailed
#Snowflake #ML (Machine Learning) #Looker #Strategy #Business Analysis #Python #Data Analysis #BI (Business Intelligence) #Redshift #SQL (Structured Query Language) #Datasets #Data Science #Cloud #Visualization #Tableau #Data Modeling #BigQuery #Forecasting #Data Warehouse #Data Engineering
Role description
Role: Data Scientist
Location: NYC, NY | Toronto, ON
Duration: Long Term
Specification:
Weβre looking for a contractor who sits between a Business Analyst and a Junior Data Scientist, focused on product analytics, financial analysis, and ad-hoc data reporting for card programs.
This is not a Data Engineer or senior DS role; we need someone who is strong in SQL, analytical thinking, and building usable insightsβnot designing pipelines or doing ML research.
This person will support product strategy and client-facing analytics with tasks.
Ideal Candidate should have experience on the below:.-
β’ 5-8 years of experience in analytics roles
β’ Worked as a Product Analyst, Business Analyst, Data Analyst, or Junior Data Scientist
β’ Significant time writing SQL and working with real-world messy datasets
β’ Some exposure to financial or transaction data (ideal but not required)
β’ Strong communication skillsβthey should be able to explain what the numbers mean
Required Skills
1. SQL (must-have, non-negotiable)
β’ Strong hands-on SQL for data analysis (joins, window functions, aggregations, date/time logic)
β’ Experience working in a cloud data warehouse (Snowflake, Redshift, BigQuery, etc.)
1. Analytical & Business Problem-Solving
β’ Comfortable turning fuzzy product questions into structured analyses
β’ Ability to interpret financial/card-program data (transactions, declines, fees, etc.)
Preferred Skills (Nice-to-Have)
Snowflake experience
β’ Exposure to Snowflake-specific SQL or warehouse concepts is ideal but not required
Python for analytics
β’ Useful for deeper explorations, forecasting, or lightweight data modeling
β’ Not a requirement
BI visualization tools
β’ Tableau or Looker strongly preferred
β’ Experience building dashboards, simple visualizations, or metric tracking reports
Payments / Card Programs domain knowledge
β’ Experience working with banking data, card transactions, or fintech analytics
β’ Understanding of digital wallets, auth flows, or settlement data is a plus
Role: Data Scientist
Location: NYC, NY | Toronto, ON
Duration: Long Term
Specification:
Weβre looking for a contractor who sits between a Business Analyst and a Junior Data Scientist, focused on product analytics, financial analysis, and ad-hoc data reporting for card programs.
This is not a Data Engineer or senior DS role; we need someone who is strong in SQL, analytical thinking, and building usable insightsβnot designing pipelines or doing ML research.
This person will support product strategy and client-facing analytics with tasks.
Ideal Candidate should have experience on the below:.-
β’ 5-8 years of experience in analytics roles
β’ Worked as a Product Analyst, Business Analyst, Data Analyst, or Junior Data Scientist
β’ Significant time writing SQL and working with real-world messy datasets
β’ Some exposure to financial or transaction data (ideal but not required)
β’ Strong communication skillsβthey should be able to explain what the numbers mean
Required Skills
1. SQL (must-have, non-negotiable)
β’ Strong hands-on SQL for data analysis (joins, window functions, aggregations, date/time logic)
β’ Experience working in a cloud data warehouse (Snowflake, Redshift, BigQuery, etc.)
1. Analytical & Business Problem-Solving
β’ Comfortable turning fuzzy product questions into structured analyses
β’ Ability to interpret financial/card-program data (transactions, declines, fees, etc.)
Preferred Skills (Nice-to-Have)
Snowflake experience
β’ Exposure to Snowflake-specific SQL or warehouse concepts is ideal but not required
Python for analytics
β’ Useful for deeper explorations, forecasting, or lightweight data modeling
β’ Not a requirement
BI visualization tools
β’ Tableau or Looker strongly preferred
β’ Experience building dashboards, simple visualizations, or metric tracking reports
Payments / Card Programs domain knowledge
β’ Experience working with banking data, card transactions, or fintech analytics
β’ Understanding of digital wallets, auth flows, or settlement data is a plus






