Wave

Associate Data Scientist

Wave • $80K — $95K *
Stamford, CT 06902In-Person
Information Technology
Less than 5 years of experience
Today
Be an Early Applicant
Job Overview by Ladders

Qualifications

  • Bachelor's degree in computer science, statistics, operations research, or related field
  • 0-3 years of experience in data analytics
  • 0-2 years of programming experience
  • Basic experience with Logistic Regression, Random Forest, and XGBoost in Python
  • Basic SQL skills
  • Strong analytical and problem-solving abilities
  • Commitment to confidentiality regarding sensitive information

Responsibilities

  • Support the end-to-end data science process including ETL, model development, and measurement of business impact
  • Partner with cross-functional teams to implement models in production and conduct enhancements
  • Assist in cleaning, analyzing large data sets to generate actionable insights
  • Collaborate with stakeholders to identify opportunities for business improvements
  • Help design and implement statistical data quality procedures
  • Communicate data science concepts clearly to team members and business leaders
  • Present findings and recommendations to stakeholders to ensure timely meeting of project goals

Benefits

  • Hybrid work schedule with opportunities to work from home up to one day a week
Full Job Description
This role requires the ability to work lawfully in the U.S. without employment-based immigration sponsorship, now or in the future.

This position is in an office environment with a hybrid work schedule. Eligible employees can work from home up to one day each week.

How You'll Make an Impact
  • Support the end-to-end data science process, including ETL, model development, validation, deployment into workflows, and measurement of business impact
  • Partner with cross-functional teams to implement models in production and conduct post-launch testing and enhancements.
  • Assist in cleaning, aggregating and analyzing large data sets to generate actionable insights
  • Collaborate with stakeholders to identify opportunities for business improvement using statistical and analytical methods
  • Help design and implement statistical data quality procedures for new and existing data sources
  • Contribute to communicating data science concepts and solutions clearly to team members and business leaders
  • Establish connections across data sources and identify new, meaningful data relationships
  • Aid in presenting findings and recommendations to key stakeholders while ensuring project goals are met on time


What You'll Bring to Spectrum

Required Qualifications

Education
  • Bachelor's degree in computer science, statistics, operations research or equivalent combination of education and experience

Experience
  • 0-3 years of experience in data analytics
  • 0-2 years of programming experience

Skills
  • Basic experience developing Logistic Regression, Random Forest, and XGBoost models in Python
  • Interpersonal, verbal and written communication skills with a focus on teamwork
  • Minimal experience with analytical and statistical software
  • Basic SQL skills
  • Strong analytical and problem-solving abilities with attention to detail and data accuracy
  • Ability to perform thorough research and analysis
  • Commitment to confidentiality and proper handling of sensitive information
  • Knowledge of computer science principles such as algorithms, data structures and design methodologies

Preferred Qualifications

Experience
  • Internship experience in a data scientist role

#LI-JV1
BDA302 2026-79974 2026

About Wave

Wave is a Canadian financial services company that provides accounting, invoicing, and payment processing software for small businesses. The company was founded in 2010 by Kirk Simpson and James Lochrie. Wave's software is used by over 4 million small businesses around the world. In 2019, the company was acquired by H&R Block for $405 million. Wave is headquartered in Toronto, Canada.
Learn more about Wave
Size
200 employees
Industry
Finance & Insurance
Founded
2011
* Ladders Estimates

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