Do you have a spidey sense when it comes to fraud?

Then Jobber might be the place for you! We’re looking for a Risk Analytics Manager to be part of our Business Operations department.

Jobber exists to help people in small businesses be successful. We work with small home service businesses, like your local plumbers, painters, and landscapers, to transform the way service is delivered through technology. With Jobber they can quote, schedule, invoice, and collect payments from their customers, while providing an easy and professional customer experience. Running a small business today isn’t like it used to be—the way we consume and deliver service is changing rapidly, technology is evolving, and customers expect more. That’s why we put the power and flexibility in their hands to run their businesses how, where, and when they want!

Our culture of transparency, inclusivity, collaboration, and innovation has been recognized by Great Place to Work, Canada’s Most Admired Corporate Cultures, and more. Jobber has also been named on the Globe and Mail’s Canada’s Top Growing Companies list, and Deloitte Canada’s Technology Fast 50™, Enterprise Fast 15, and Technology Fast 500™ lists. With an Executive team that has over thirty years of industry experience of leading the way, we’ve come a long way from our first customer in 2011—but we’ve just scratched the surface of what we want to accomplish for our customers.

The role:

The Risk Analytics Manager will be an integral part of the Business Analytics team supporting Risk operations within the Fintech area of Jobber’s business. This position will have a mix of strategic and operative responsibilities that multiply Jobber's ability to protect against credit losses while adding a data focused approach to risk decision making. Risk Mitigation is a very important area of Business Analytics service offering and as such, prior experience in thought leadership positions in the area of Risk Analytics is essential for success.

The area of support:

Fintech is one of the fastest-growing parts of Jobber, and a core strategic priority for us as a company. We're investing in this growing area because we believe embedding financial tools within our product deepens our ability to help small businesses be successful. Whether it’s helping small businesses get paid, offering financing to their customers, or accessing capital to invest in growth – we believe small business owners should have seamless access to financial tools that allow them to thrive.

Our Risk operations - a key group within the broader Fintech area - is central to Jobber’s success, focused on keeping both our Jobber Payments customers and Jobber safe.

The Risk Analytics Manager will be fully responsible for all analytical work performed in the area of Credit Risk, including:

Data Process-Flow and Systems Integration

• Spearhead the integration of data, analytics-related processes, and ML-driven strategies & data flows within user-decisioning and case management systems (e.g. Unit 21 etc.)
• Champion the streamlining, standardization, and automation of risk data management processes
• Champion the initiatives designed to ensure completeness and accuracy of risk-related data

Development & Optimization of Loss Prevention Systems

• Design, build and maintain analytics-driven Loss (chargebacks and/ or fraud) Prevention Systems, e.g. systems for Behavioral Anomaly Detection, operative monitoring for Early Warning Indicators, and other data-driven solutions that help proactively detect and effectively prevent possible credit and fraud losses
• Optimize existing systems through ongoing analysis of behavioral data to uncover new patterns of fraud or other financial risk
• Optimize performance across Acceptance, Monitoring, Chargeback and Recovery processes via regular review of the rules, parameters and thresholds

Strategic Thought Leadership & Decision-Making Support

• Support strategic decisioning in the area of Fraud and Credit Risk Management through in-depth data-driven analysis and strategic consulting on the risk prevention strategies (e.g. trade-offs between risk reduction and customer experience impacts)
• Proactively alert the stakeholders of the possible risks and opportunities for improvement to power corrective action on risk tools and technology platforms
• Identify, design and implement the informational systems that would support monitoring and reporting on the state of credit risk in a timely and efficient manner - to both operational and financial stakeholders at different levels within the organization

Cross-Functional Leadership & Collaboration

• Support the design of the ML / AI solutions by providing Data Science Team by providing guidance, subject matter expertise, and custom-analytics insights
• Deeply understand current and future data needs and communicate and prioritize them with data infrastructure teams
• Closely collaborate with the Business Intelligence team on the implementation of the Credit Risk BI solutions

To be successful, you should have:

• 5+ years of analytical experience in the area of credit risk, fraud detection or equivalent, preferably in the capacity, that combines functional and / or project leadership with full hands-on analytical execution via programming tools
• Strong SQL skills and ability to efficiently manipulate complex database structures for analysis
• Experience in integration of data & analytics within Risk Case Management Systems
• Python/ R skills and Machine Learning experience are an asset
• Experience with BI tools (Mode, Tableau, Power BI or equivalent) is an asset
• An analytical mindset and strong statistical skills. Ability to review and find trends in transactions and usage for signs of fraud or abnormalities, and quantify trends in the data by applying statistical techniques
• Clear communication skills. You’ll be dealing with multiple stakeholders in the company on complex quantitative issues, so being able to translate and communicate your ideas and findings clearly will be important
• The ability to embrace ambiguity. We don’t know what we don’t know, so you should be comfortable coming in and improving the process
• The ability to work autonomously. We’re currently working remotely, so while you’ll be a member of a team and there are connection points, you’ll be on your own for a majority of the day. You’ll need to be a self-starter, with the ability to make decisions and find direction and guidance