Data Scientist(worked prior as Data Analyst)

Company: Jobs via Dice

Location: Location not specified (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-05-07

About this role

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Synergent Tech Solutions, is seeking the following. Apply via Dice today!


Note: Need Senior/Lead Data Scientist only here - 12\_ Years of Exp
Role: Data Analyst / Scientist
Remote
Job Description:


Data Wrangling & Preparation

  • Clean, normalize, and QA complex datasets (ex: credit card transaction files)
  • Build reproducible data pipelines and queries
  • Use of LLM s to clean and standardize credit card transaction data

Analytics & Insights

  • Conduct exploratory data analysis to surface trends and opportunities across member segments, tiers, earning patterns, benefit usage, etc.
  • Develop clear, actionable insights to support marketing and cobrand decisions.
  • Support ad-hoc analyses, including member behaviour, spend behaviour, and partner activity
  • Develop interactive, user-friendly analytical applications using Snowflake Cortex + Streamlit in Snowflake.
  • Nice to have: Ability to build scalable, production-ready ML workflows in Snowflake (Snowpark, ML Functions, Feature Store), including end-to-end pipeline development encompassing data preparation, feature engineering, model training, testing, deployment, evaluation, and ongoing monitoring.

Dashboarding & Reporting

  • Design and build dashboards (Tableau) that provide intuitive visibility into KPIs, member engagement, and program performance.
  • Refresh and maintain reporting assets, and improve existing dashboards as needed.

Qualifications

  • Strong SQL and intermediate python skills
  • Experience building dashboards using Tableau
  • Experience using LLM s for data manipulation is a nice to have, however a drive to learn quickly is a must have
  • Experience building analytical applications using Snowflake Streamlit is a nice to have
  • Demonstrated ability to clean and work with messy datasets (credit card data, transactional records, etc.).
  • Ability to support model deve...

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