Company Description
Curinos empowers financial institutions to make better, faster and more profitable decisions through industry-leading proprietary data, technologies and insights. With decades-long expertise in the financial services industry and a relentless focus on the future, Curinos technology and analytics ecosystem allows clients to anticipate customer needs and optimize their go-to market decisions in an increasingly competitive market.
Curinos is operating under a hybrid modality. This individual may work from the Toronto office.
All candidates must possess work authorization which does not (and will not in the future) require work sponsorship by an employer.
Job Description
Curinos is looking for an experienced applied Staff Data Scientist to join our Data Science & Machine Learning Team focused on the application of data science, machine learning and AI approaches to understanding banking customer behavior and optimizing engagement marketing through our FinTech product platforms! You’re passionate about finding patterns, trends, and opportunities that can enable a better consumer banking experience, curious about what is driving KPIs and customer outcomes, and insightful in your analytical approach. You thoughtfully bring data science-based insights into the conversation about our customers and pursue improvements proactively, while building on shared cross-functional knowledge and expertise.
As a Staff Data Scientist, you are an influencer who can up-level the pursuit and impact of applied data science at Curinos, formulate and implement company-wide best practices, and lead large scale initiatives end to end.
Responsibilities
- Combine data sources and apply multiple data and algorithmic approaches to create a clear, cohesive, static and temporal picture of banking customers, actionable for both humans and algorithms.
- Collaborate with business partners to develop meaningful segments to target and optimize consumer interactions based on shared preferences and behaviors.
- Partner with our machine learning engineers to refine and extend our Reinforcement Learning-based marketing optimization capabilities.
- Act as the main contributor for implementing modern ML solutions to address complex banking use cases. Able to effectively distribute the knowledge across the team to promote growth.
- Create well-organized datasets and data processing, algorithm implementations and recommended visualizations that can support implementation in our platform software and documentation, feature and functionality descriptions and customer engagement as needed
- Proactively guide team on appropriate algorithmic approaches that are well fit for different problem spaces. Enforce best practices on model training, model evaluation, and model promotion/monitoring.
Qualifications
- You have 5+ years' experience and a demonstrable track record of delivering applied machine learning or data science capabilities in consumer-facing and/or enterprise applications.
- You have independently prototyped, optimized, validated, managed, operated and updated machine learning and statistical models.
- You can demonstrate knowledge of statistical inference, experiment design, probability, sampling methodologies, regression, classification, clustering, data mining, multi-armed bandits, time series analysis, causal inference analysis, neural networks and deep learning techniques.
- You have familiarity with GenAI concepts including retrieval augmented generation or fine tuning.
- You have a strong working knowledge of Python-based machine learning frameworks and the data and computation management mechanisms that surround them in a cloud setting (experience with PySpark and Databricks preferred).
- You have exceptional communication skills that can be delivered in the context of your audience from deep science to business decision-makers.
- You possess strong interpersonal skills and an ability to influence others around you towards data-driven business goals.
- You can quickly pivot and act with agility as dictated by the needs of the business.
- You hold an advanced degree or equivalent career experience in Computer Science, Applied Mathematics, Statistics or a related technical discipline
Additional Information
Why work at Curinos?
- Competitive benefits, including a range of Financial, Health and Lifestyle benefits to choose from
- Flexible working options, including home working, flexible hours and part time options, depending on the role requirements – please ask!
- Competitive annual leave, floating holidays, volunteering days and a day off for your birthday!
- Learning and development tools to assist with your career development
- Work with industry leading Subject Matter Experts and specialist products
- Regular social events and networking opportunities
- Collaborative, supportive culture, including an active DE&I program
- Employee Assistance Program which provides expert third-party advice on wellbeing, relationships, legal and financial matters, as well as access to counselling services
Applying:
We know that sometimes the 'perfect candidate' doesn't exist, and that people can be put off applying for a job if they don't meet all the requirements. If you're excited about working for us and have relevant skills or experience, please go ahead and apply. You could be just what we need!
If you need any adjustments to support your application, such as information in alternative formats, special requirements to access our buildings or adjusted interview formats please contact us at [email protected] and we’ll do everything we can to help.
Inclusivity at Curinos:
We believe strongly in the value of diversity and creating supportive, inclusive environments where our colleagues can succeed. As such, Curinos is proud to be an Equal Opportunity Employer. We do not discriminate on the basis of race, color, ancestry, national origin, religion, or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other protected characteristics.
