SentiLink

Account Executive

• Proactively reach out to prospective partners to discover companies that we can serve
• Own the sales process by leading meetings, building relationships, marshalling SentiLink resources to deliver solutions, preparing analytical business cases, and closing commercial agreements
• Navigate complex organizations to align with decision makers and build champions within prospects and partners
• Continue to drive value to our partners post-close by owning relationships and helping our partners be successful with our solutions
• Represent SentiLink in accordance with our corporate values at all times

Growth Account Executive – Fintech

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Enterprise Account Executive

Customer Success Manager

• Own the relationships for strategic accounts across our bank, credit union, and fintech customers
• Develop an extremely in-depth understanding of the fraud domain and SentiLink’s products
• Handle onboarding activities: dashboard training, account setup, setting initial SentiLink usage recommendations, etc.
• Meet with customers on a regular basis after onboarding (sharing performance data, product updates, exploring new products, handling renewals)
• Take a consultative approach - be able to understand what fraud situations partners are dealing with, and come up with potential solutions (even if it doesn’t include SentiLink’s own products!)
• Establish business goals with each client and establish a plan to achieve targets

Strategic Customer Success Manager

• Build pipeline through cold outreach and follow-up on warm leads generated by marketing
• Own the full sales process end-to-end: first meeting, demo, trial, negotiate, and close
• Represent SentiLink’s new product offerings at industry events, tradeshows, and conferences

Founding Account Executive

Data Scientist

• Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring.
• Research new types of fraud and develop new SentiLink products around identity verification.
• Build foundational modeling to drive SentiLink’s expanding suite of Fraud and Financial Risk products.
• Achieve success by researching / developing through iteration, integration of new data sources and inventive feature engineering.
• Write production-ready code that can be relied on for real-time decision making by our partners.
• Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts.
• Work with engineering, risk operations, and data acquisitions to access necessary data, maintain data quality, and support data access

Data Scientist 2 – Full Stack

Account Manager

• Deliver substantial ARR growth with our alliance partners, using a combination of marketing, channel sales, and ongoing account management
• Build and execute against alliance growth plans outlining strategies to generate ARR growth through each alliance
• Lead QBRs, pipeline reviews and ongoing business planning with alliance partners
• Support retro studies and the pre-sales process alongside alliance sellers
• Host ongoing partner enablement sessions to educate sellers, CSMs and product teams
• Build and maintain relationships with key stakeholders across alliances, including sales, customer success and product
• Support technical integrations into partner platforms based on SentiLink best practices

Channel Partnerships Manager, Fraud & Identity

Manager

Alliances Manager

• Build out our foundational processes for generating and surfacing model performance metrics, including crafting + calculating the metrics and building python rails.
• Act as point of contact for Strategic Financial Partners and manage their model governance needs. Regularly conduct performance and exploratory analyses to establish the quality of model outcomes.
• Providing guidance on the appropriate use of our products, respond to inquiries around model development procedures and generate stability analyses.
• Create automation to detect inconsistencies or issues with the production models that power our fraud detection products, such as data driven gap analysis to automation via anomaly detection or training challenger models to identify weaknesses.
• Primarily work with a Python ecosystem, using SQL, SageMaker, S3, Metabase and Git to support.

Model Risk Data Scientist

Business Operations

• Work on ad-hoc projects as directed by the CEO, supporting and collaborating with a wide range of functions (e.g. Go-To-Market, Finance, Product) depending on business needs.
• Support and elevate SentiLink’s annual planning process, monthly business reviews, ongoing goal-tracking, and other business cadences.
• Manage, improve, and track business KPIs that give insight into company-wide progress and execution.
• Prepare materials for board meetings, executive presentations, and other high-level communications.

Strategy & Business Operations Associate

Product Manager

• Own the product vision, roadmap, and execution for internal technical initiatives, with a strong focus on data‐intensive systems and foundational datasets.
• Lead cross-functional efforts to improve the quality, reliability, and usability of internal systems, including datasets, shared services, and internal platforms.
• Drive long-term initiatives to future-proof internal data and technology assets, ensuring they scale with evolving product, analytics, and operational needs.
• Partner with engineering, data science, solutions analytics, and product stakeholders to understand use cases, clarify requirements, and identify interdependencies.
• Manage prioritization across competing internal demands, balancing immediate impact with long-term strategic value.
• Translate complex internal needs into clear, actionable specifications and ensure alignment across teams.
• Apply structured project management to initiatives with multiple teams, ambiguous problem spaces, and intricate technical dependencies.
• Define and track success metrics for internal systems and datasets, such as quality, completeness, latency, reliability, and stakeholder satisfaction.
• Communicate roadmap, progress, risks, and tradeoffs to internal stakeholders at all levels.