- Ottawa, ON, Canada
- Employees can work remotely
At thinking Capital, we’re changing the landscape of financial technology!
Simply put, our mission is to empower Canadian small businesses through innovative financial services. At the heart of our offering is our digital experience, which is powered by our proprietary software platform, our real time connections to a multitude of data sources and our advanced data science models. We are squarely in the corner of owners and entrepreneurs, providing for them, and at the right moment, the financial support they need to grow and thrive.
You have spent countless hours over the years solving hard problems in mathematics, statistics and computer science. You thrive on extracting useful information from large messy data sets. You know that a data set that satisfies all the requirements of a specific statistical procedure is a rarity indeed – and you know what to do about it. You have followed your passion for all things quantitative and are turning it into your profession.
At ThinkingCapital we encourage everyone to trust themselves, stop holding back and use your acquired knowledge to influence your future. Everyone in the team is an integral contributor to our products, working with our customers to collaborate and design the best solutions.
Our open work culture provides the opportunity for you to contribute to all aspects of our business: customer engagement, product ownership, software, QA, devops and 24/7 cloud service deployment.
As a key member of our team your passion for data will help us design, develop and deploy our integrated cloud services that help small businesses succeed.
What you'll do:
• Application of machine learning to an automated financial services platform
• Design of sophisticated algorithms that work on large datasets in real-time
• Learn and adapt emerging machine learning methodologies to real problems
You bring strong knowledge and real-world experience:
• Machine learning and artificial intelligence
• Statistical methodology (eg linear & logistic regression, time series models, hypothesis testing, etc)
• Python (Pandas), R (tidyverse) and SQL
• Algorithms, data structures, and computational mathematics
• Experience with analytics for large messy data sets
• Obtaining data from web sites via scraping, apis and third parties
• Proficiency with Linux command-line
• Working autonomously and being highly resourceful
• A masters degree in statistics or equivalent
We value data scientists who can demonstrate personal or business projects that have solved real problems big or small with data sets that you have obtained. You found the right data, scraped it off a web site or used an api to get it. Stored it, munged it, found all the anomalies and figured out what to do about them. You asked statistical questions of the data, found out that the data did not satisfy the requirements of the methodology you used, and figured out what to do about that. You derived useful information from the data and demonstrated value from the project.
Why you should join us:
Surround yourself with a high-performing, energetic and passionate group of people dedicated to the Thinking Capital Mission.
Be part of a team that is revolutionizing the financial system and redefining how Canadian small businesses access capital.
Take on complex projects in an innovative, start-up-like environment.
Benefit from an amazing working environment offering you the flexibility to do your best work
Diversity of thought:
Join a team that values diversity and collaboration.
Thinking Capital is a leader in the Canadian FinTech industry and Canada’s largest non-bank lender to small businesses. Since its inception in 2006, the company has enabled over 16,000 businesses to quickly, conveniently and securely access capital to grow.
The company has offices in Montreal, Toronto and Ottawa. Thinking Capital is a subsidiary of Purpose Financial, a diversified financial services platform focused on addressing historically underserved segments of the market. Purpose is backed by OMERS, TorQuest Partners and now Allianz.