Technical Account Manager - Toronto, Canada at DataVisor

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

26 Jun, 26

Salary

120000.0

Posted On

28 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Product Support, Escalation, Resolution, Machine Learning, Rule-Based Solutions, Solution Deployment, Use Case Understanding, Integration Management, Implementation Process, Business Reviews, Product Roadmap Communication, Technical Ambassador, Communication, Presentation, Time Management, Project Management

Industry

Software Development

Description

About DataVisor DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's solution scales infinitely and enables organizations to act on fast-evolving fraud and money laundering activities in real-time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide guaranteed performance lift from day one. The flexible architecture of DataVisor's platform allows enterprises to power sophisticated and complex use cases across different businesses while dramatically lowering the total cost of ownership. DataVisor is recognized as an industry leader and has been adopted by Fortune 500 companies globally across many industries. Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us! Position Overview As a Senior Technical Account Manager (TAM), you will manage a portfolio of client relationships and establish yourself as a trusted technical advisor and solution partner for the key leaders within the customer’s fraud and risk teams. You will partner with our Delivery Team to oversee the customer’s data integration and onboarding process. Your goal is to ensure that the customer adopts best practices in the implementation of our platform to ensure they extract the maximum value from their investment. You will engage in broad ranging topics from assessing/debugging platform performance or product functional issues, provide technical guidance and best practices, or advise on customer’s use of custom or DataVisor built machine learning models and/or automation rules to detect suspicious activities. You will work cross-functionally with Customer Success, Engineering, and Product teams to achieve your goals. Key Responsibilities Provide product support, escalation, and resolution of technical issues Architect machine learning and rule-based solutions for customers’ fraud problems Lead solution deployment deep dive discussions in late stage pre-sales calls Understand client use cases and define plans to achieve success criteria Manage integration and product implementation process for customers Conduct and coordinate business reviews and presentations with clients Drive product roadmap by communicating client feedback to internal teams Attend meetups, events, and conferences as a technical ambassador 8+ years of experience in banking, payment, social, or e-commerce industries, as customer facing technical roles e.g. technical account manager or solution consultant B.A./B.S. degree in a technical or analytical discipline Excellent communication and presentation skills Strong time and project management ability with focus to ensure deadlines are met Experience in fraud detection and risk management is a big plus Coding and database experience (e.g. Python, Java, SQL) a plus Based in Ontario, Canada Compensation: Annual salary range of CAD70K to CAD120K PTO, stock option

Responsibilities

The Senior Technical Account Manager will manage client relationships, acting as a trusted technical advisor for fraud and risk teams, and partner with the Delivery Team to oversee data integration and onboarding. Responsibilities include providing technical guidance, assessing platform performance, and advising on the use of machine learning models and automation rules.