Senior Data Scientist - Predictive Analytics & CLV

momentumfinancialservicesgroup; Toronto; Hybrid; CAD 120,000 - 155,000; Full time

Benefits offered by this job

Discretionary bonus

Comprehensive benefits

Retirement plans

Hybrid work environment

Tuition assistance

Perkopolis discounts and rewards

Job summary

Momentum Financial Services Group is seeking a Senior Data Scientist to consult with the business, identify opportunities, and implement advanced analytics and data science solutions that drive measurable value. You will work with product, marketing, and technology teams, reporting to the Senior Director of Data Science.

You will develop predictive and prescriptive models, lead CLV initiatives, and ensure data integrity while aligning with regulatory and audit requirements.

Qualifications

• Experience developing, validating, implementing, monitoring, and refining predictive models.
• Demonstrated ability to translate business questions into data-driven solutions.
• Strong background in finance-related analytics and ML techniques.

Responsibilities

• Design, develop, validate, and implement predictive models addressing business needs.
• Lead CLV modeling efforts and collaborate with Product, Marketing, Finance teams.
• Provide data-driven insights through ad hoc analytics and complex data exploration.
• Monitor model performance and retrain as needed to maintain accuracy.
• Collaborate across departments to deliver data-driven strategies for risk and performance.

Skills

Predictive modeling

Model validation

Model deployment

Statistical analysis

Econometrics

Education

Master's degree with 5+ years

PhD with 2+ years

Job description

Momentum Financial Services Group is seeking a Senior Data Scientist to consult with the business, identify opportunities, and implement advanced analytics and data science solutions that drive measurable value. You will work with product, marketing, and technology teams, reporting to the Senior Director of Data Science.

You will develop predictive and prescriptive models, lead CLV initiatives, and ensure data integrity while aligning with regulatory and audit requirements.