Pre-Sales Solutions Architect

Job Description

About Us

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. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

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

We are looking for a Pre-sales Solution Architect to lead the solution architecting and integration scoping in the mid-to-late stage of the pre-sales cycles. You will be driving technical  discussions and deep dives with the customers’ risk business teams (Fraud and AML), data team, system architect team, Engineering team, and info security team, to present DataVisor system architecture and integration options, discover integration-related business and technical needs, design and propose integration architecture. You will use your strong business acumen and technical knowledge to get to alignments with the customers, and document the integration proposals for the post-sales execution to be based on. You will provide proper handover to post-sales teams e.g. Delivery, Customer Success, Data Science, to ensure they fully understand the scope, business requirements and integration plan.You remain as a big stakeholder in the deployment phase and see it through to make sure the customers get the expected outcome from the integration plan. You will work closely with multiple teams within DataVisor, e.g. Account Executives (AE), Sales Engineers (SE), Delivery, Product, Engineering, Customer Success, and Data Science.. 

Requirements

Key Responsibilities

• Integration Requirement Discovery: Work closely with the Account Executive (AE) and Sales Engineer (SE) to discover and understand the customer requirements regarding integrations, e.g. data sources to integrate with, 3rd party systems to integrate with, real time and/or batch integration needs, turnaround time and latency requirements, high availability requirements, security requirements. 
• Technical Integration Meetings: Manage and drive external and internal meetings throughout the Integration Scoping and Planning phase. Align with various client stakeholders and DataVisor teams to ensure the proposed plan meets customer requirements, both business and technical, and are compatible with DataVisor system architecture. 
• Knowledge Handoff and Technical Escalation: Use standard documentations to conduct knowledge transfer and internal Q&A sessions with DataVisor post-sales teams e.g. Delivery, Customer Success, Engineering, and Data Science. During the onboarding phase, serve as the technical escalation point for customers in case issues and misalignments happen during the delivery phase. 
• Demo and POC Environment Setup: Own the solution demo environment to make sure it’s properly configured with the latest and greatest product functionalities. Own the POC environment setup tasks for the DataVisor platform POCs, including tenant creation, user access setup, data loading, out-of-the-box rules creations, case review system default setup configurations.   
• Domain and Product Expertise: Stay updated on industry trends and emerging technologies, particularly in financial services, fraud prevention, AML practices, and machine learning, to provide cutting-edge solutions to clients. Stay updated on product knowledge, product configuration best practices, workarounds for known issues. 
• Presentations & Demonstrations: Conduct presentations and demonstrations to explain proposed solutions and configurations to clients and stakeholders.

Qualifications

• Experience: 
• 3+ years of experience in customer-facing SaaS project implementation roles e.g. Solution Implementation Engineer, Technical Project Manager. 
• 3+ years of experience in working with Real Time data integrations (e.g. RESTful API and Kafka) and batch data integrations (e.g. SFTP, cloud bucket) with core banking systems, relational databases, and data warehouse products.
• 2+ years of experience in utilizing or implementing risk management tools that have a rules engine and case review system.  
• Technical Knowledge: 
• Domain expertise in system architecture of SaaS platforms 
• Domain expertise in system integrations and data integrations
• Domain expertise in API and UI authentication, and data encryption
• Domain expertise in anti-fraud and AML systems in the financial industries 
• Familiarity in fraud/AML data structure and operation workflows
• Soft Skills: 
• Excellent communication and interpersonal skills
• Client management, expectation setting, objection handling, consulting skills.
• Ability to convey complex technical concepts to non-technical audiences, and switch between technical and business centric discussions
• Creative problem-solving skills and a results-driven mindset
• Ability to work collaboratively in a team environment and manage multiple projects simultaneously.
• Education: 
• Bachelor’s degree in a technical or analytical discipline e.g. Engineering, Statistics, Computer Science

Benefits

Competitive compensation, Stock options, 401k, Health Benefits.

Amazing company culture and work environment.