Join an exciting team of data scientists and engineers at the forefront of using data to drive decisions at every level of our organization.
The insurance industry is undergoing a transformation and you get to be in the driver’s seat of this data-driven, technology revolution.
You will work on impactful projects focusing on detecting fraudulent activities and machine learning-based fraud engine to find new and innovative ways to impact our customers.
As a data scientist, you will be part of the Fraud Data Science team with exposure to different business partners and direct influence on future products and innovative solutions.
You will take part in the end-to-end SDLC process from ideation to production support to model monitoring. You will be developing and deploying data pipeline, machine-learning and statistical models for practical applications that impacts millions of customers.
The team has already developed algorithms used in production systems and you will be part of the team that expands the scope of these algorithms.
This is your chance to join the InsureTech revolution!
What you'll do
Develop, test, and deploy code
Maintain an existing code database
Transformation of complex data sets into meaningful conclusions & recommendations
Develop innovative solutions for pattern recognition using machine learning and statistical approaches
Communicate actionable recommendations based on insights / model results
Driving co-ordination / delivery accountability of project and BAU delivery based on timelines & direction
Driving conformance / Alignment to IT / Enterprise Architecture standards (where applicable)
Design and deploy the models to real-time APIs
What you'll bring
As a data-scientist, you will need the following skills and experience to succeed in the role :
An educational background in computer-science or engineering, math, statistics, physics or related field. A minimum of MSc is required and Phd preferred.
2+ years of experience in end-to-end model development life cycle and working with large datasets. This can include experience from any industry or academia (post-doc experience).
2+ programming experience in Python with good grasp of software engineering standard methodologies such as code-reusability, modularity, use of repos, etc.
Proficiency with SQL and Git (2+ years)
Experience with PostgreSQL, Teradata, Hadoop and AWS is an asset.
2+ years of experience productionalizing models, model monitoring and MLOps
1+ years of expertise in building and configuring production-ready machine learning systems
Conceptual understanding in a data-driven software engineering environment and how to leverage data to make business decisions.
A track record in building and maintaining high quality, robust and maintainable code.
Familiarity with CI / CD is a bonus
Understanding of Data Warehouse concepts, ETL strategies and best practices.
An appetite for problem solving with a creative and resourceful approach to finding the right solution for the job.
Prior fraud and insurance experience is a bonus
Experience in consuming and building APIs is a bonus
A high level of comfort using Git
Strong communication and collaboration skills
What sets you apart
A growth mindset with versatile skills and able to work through problems from first-principles.
A portfolio of projects that demonstrate your ability to draw inferences from data. This includes participation within the broader data science community including Kaggle competitions or any personal projects with open data.
A can-do teammate who is willing to roll-up the sleeves and do whatever is needed to move projects forward. That means at times you will wear different hats and be a project manager, developer, modeler and chief communicator of solutions.
Amazing people skills and able to translate and communicate complex algorithms to non-technical individuals. Someone who understands that it is not enough to just have a phenomenal algorithm but meaningful to build an agreement for the solution from different partners.
The best problems in the industry are yet to be articulated. We need someone who is creative, self-motivated and can lead projects independently.
Additional Information
Aviva Canada is committed to providing accommodations for people with disabilities during all phases of the hiring process including the application process.
If you require an accommodation because of a disability, we will work with you to meet your needs. Applicants need to make their needs known in advance.
If you are selected for an interview and require an accommodation, you are encouraged to advise the Talent Acquisition Partner who will consult with you to determine an appropriate accommodation.
Data Scientist I.
The Data Scientist, Advanced Analytics role within the Commercial Growth Strategy & Execution Department reports directly to the Senior Manager, Data Science. The team is responsible for fostering a data-driven culture at Coke Canada, supporting analyses across categories, brands, channels, customer...
Lead Data Scientist
As the Lead Data scientist within the Data & Analytics team at Equifax Canada, you will be critical to driving Data Science innovation, working closely with the rest of the Canadian Equifax Data Science & Insights team and the Data Science community internationally. You will extract the data you nee...
Data Scientist
Partner with data engineering and data analytics teams to ensure that data structures and data pipeline enhances data science applications and shortens development cycle. We are looking for an experienced Data Scientist to join our team. You will report to the Manager, Data Science. Monitor and depl...
Data Scientist
We’re looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. As Data Scientists as Stripe, it’s our mission to ensure that the company strategy, products, and user interactions make smart use of our ri...
Data Scientist, Value Assurance
Actionable Insights, Analytical Statistics, Analytics Insights, Critical Thinking, Data Administration, Database Structures, Data Mining, Data Modeling, Data Movement, Detail-Oriented, Group Problem Solving, Quantitative Research, Research Documents, Storytelling, Strategic Objectives, Teamwork. Lia...
data scientist
Research and document data requirements, data collection and administration policy, and data access rules. Design methods of collecting and processing data to answer specific research questions. Research data collection and administration policy. Develop and implement data administration policy, sta...
Senior Data Scientist - Brand
Our highly skilled team of data scientists and machine learning engineers specialize in developing algorithmic solutions for notification and recommender systems, advertising attribution, and LTV predictions. As a Data Scientist on the Brand team, you will develop the intelligence behind our efforts...
Senior Data Scientist
Reporting to the Director, Strategic Intelligence and Predictive Analytics and with occasional direction from the AVP Institutional Planning and Chief Data Officer, the Senior Data Scientist role applies a combination of techniques from statistics, machine learning / artificial intelligence, compute...
Senior Data Scientist, Rider Segments
As a Senior Data Scientist in the Rider team, you will leverage data and rigorous, analytical thinking to shape our rider app and make business decisions that put our customers first. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building algorithm...
Scientifique des Données Sénior.e / Senior Data Scientist
We're looking for a thoughtful and disciplined Data Scientist with deep statistical modeling experience, strong data engineering experience and a passion for games and digital technologies. You will report to a senior data science manager within EA's central Data and Analytics (DnA) organization. Ef...