data scientistdata scientist - Canada - Brain Finance

Description

We are looking for a talented, enthusiastic, and results-driven Data Scientist to join our growing team who will be responsible for responding to analytics requests, managing data assets, and developing predictive and forecasting analytics solutions in support of the organization's lending decisions across all aspects of Growth, Marketing, Product, Credit, Operations, and Finance.

Brain Finance is a leading financial technology company providing responsible and constructive credit solutions to consumers. We are redefining access to credit with our revolutionary technology that uses machine learning and automation capabilities to deliver better, simpler financial services to everyone

We are looking for a talented, enthusiastic, and results-driven Data Scientist to join our growing team who will be responsible for responding to analytics requests, managing data assets, and developing predictive and forecasting analytics solutions in support of the organization's lending decisions across all aspects of Growth, Marketing, Product, Credit, Operations, and Finance.

The ideal candidate should have a strong academic background in data mining and predictive modeling.

The candidate should have a great sense of data and ideally would have some relevant experience in the lending, credit, fraud, banking, and financial services industries.

Develop actionable analytics insights for continuous enhancement of lending business management in all aspects of credit risk, policy and strategy, marketing and sales, account behavior, and collections.

Monitor portfolio performance and drive validation of analytics solutions and adjustments of credit and marketing/sales strategies to mitigate risk.

Strong familiarity and experience with Machine Learning algorithms; The Python Data Science stack is mandatory; Regression, Clustering, SVM, Decision Trees, DNNs, Recommendation Algorithms, etc.

Respond to ongoing analytics and data requests from all areas of banking.

Work with credit and operations engineering and database management teams to implement analytics solutions and improve our underwriting processing and account management.

Exploratory data analysis employing large data sets involving visualization and basic statistical techniques to develop intuitions and identify key variables in data science projects
Serve as an expert consultant to senior management on highly complex issues.
Work with the executive team to match communications strategies with organizational strategies and objectives.

Learn and understand the business in detail and educate the organization in the use and understanding of analytics and data.

4+ years of experience in data processing and predictive model development with strong analytical, conceptual, and quantitative problem-solving skills.

~ Sc Degree, preferably in a quantitative area such as statistics, mathematics, computer science, engineering, or economics.
~ Highly skilled in Python Data Science Stack (NumPy, SciPy, Pandas, Scikit-learn, Jupyter, IPython), Machine Learning and Statistics, Data Visualization, A/B Testing, Bandit problems, Recommendation systems, and Reinforcement learning.
~ Expertise in SQL and NoSQL databases, including Google BigQuery/BigTable, PostgreSQL, and MySQL. As well as knowledge of a GraphQL query language for APIs.
~ Good understanding of the unified artificial intelligence platform Vertex.
Knowledge of external credit/alternative data for assessing credit outcomes is a plus.
~ As we provide the majority of our services in 7 provinces in Canada, the candidate must be able to communicate effectively in English to fulfill their duties.

Group Insurance (Health and Dental)
Retirement Savings Plan (RSP)
Flexibility to work remotely from Montreal or at our office.
Paid training subscription tools.
Weekly 5 to 7s and office activities
Office Perks (fresh fruits, snacks, games, yoga and meditation room)

Schedule: 8-hour shift.


Job Types:
Full-time, Permanent.

Ability to commute/relocate:
Montréal, QC, reliably commute or plan to relocate before starting work.
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