Undergraduate degree in Statistics, Mathematics, Computer Science, or a related field.
2-4 years of experience in applied statistics or machine learning model development.
2-4 years in data wrangling, including SQL for integrating data from multiple sources.
2+ years of programming experience with SQL and Python or R.
Proficiency in operational procedures and workflows.
Responsibilities
Participate in the full data science lifecycle from problem understanding to model deployment.
Perform data extraction, wrangling, and exploratory analysis.
Train and evaluate statistical and machine learning models.
Develop scripts for batch and real-time model output delivery.
Maintain deployed models, ensuring proper output and debugging when necessary.
Benefits
Hybrid work environment, allowing flexibility between home and office.
Support for financial health with employee share purchase plan and pension benefits.
Flexible health benefits and wellness programs from day one.
Career growth opportunities through education assistance and leadership training.
Community commitment with donation matching and volunteer days.
Full Job Description
The primary role of Data Scientist 2 is to participate in the data science lifecycle to develop and deploy analytical models. Tackle a breadth of challenges from wrangling data, finding the optimal model fit, to delivering results to our business stakeholders.
If you are great at:
Participate in the data science lifecycle from understanding the business problem, to data extraction, to model development, to production deployment and change management
Perform data extraction and wrangling, and conduct exploratory data analysis
Train and evaluate applied statistics and machine learning models, using open source and cloud based proprietary software
Develop deployment scripts for batch and real-time delivery of model output
Maintain deployed models by running and delivering model output and debugging scripts as needed
If you have:
Undergraduate degree in Statistics, Mathematics, Computer Science, or relevant field
2-4 years of professional experience in applied statistics and/or machine learning model development and implementation
2-4 years of professional experience in data wrangling and feature engineering, including SQL writing queries to integrate data from multiple sources
2+ years of programming experience with SQL and Python/R
Proficiency in operational procedures, workflow, and processing functions
Experience in scalable data engineering, software engineering and/or MLOps practices is an asset
We really mean it when we say we put you first. Here are a few ways how:
Hybrid work! You get to work from the office and at home 50/50, allowing you to manage both worlds with the ease and flexibility you need.
We offer competitive salaries and support your financial health through our employee share purchase plan, pension plans, RRSP, discounts on staff insurance, and more!
We help you prioritize your well-being from day one through flexible health benefits, early leave days, wellness programs, rewards, and recognition programs.
We are invested in helping you grow in your career through education assistance to complete your CIP, FCIP, CRM or other courses desired, internal mobility, Leadership training and mentoring programs.
NBFC cares about the community and supports the causes you believe in with donation matching and team volunteer days.
We9re committed to pay transparency and fairness. The base salary range for this role is $84,000-$126,000, reflecting expected base pay - not the total compensation package. Actual base salary may vary depending on your experience, skills, and alignment with the position. We9re also open to candidates at different levels, so if this range doesn9t quite match your expectations, don9t let that hold you back - we9d still love to hear from you.
This is a real opportunity - we9re actively hiring! If the role sounds like a good fit, we encourage you to apply. Beyond base pay, we offer a robust Total Rewards program that includes benefits, wellness support, and other meaningful perks.
We also want to be transparent about our hiring process. While one of our systems includes AI capabilities, over 99% of our screening is done by real people. We believe in thoughtful, human-centered hiring decisions and are committed to giving every application the attention it deserves.
