[Remote] Product Manager, Data and Internal Products at SentiLink

United States

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Not SpecifiedCompensation

N/AExperience Level

N/AJob Type

Not SpecifiedVisa

N/AIndustries

Requirements

5+ years of product management experience with data-heavy or platform-oriented products
Hands-on experience working with large datasets, ideally in distributed or big-data environments (e.g., Spark, Databricks, BigQuery, Snowflake, similar)
Strong understanding of big data concepts, data pipelines, data cleaning/normalization, and data modeling
Demonstrated ability to partner effectively with cross-functional teams, including engineering, data science, solutions analytics, and product stakeholders

Responsibilities

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

Skills

SentiLink

Machine learning solutions for identity fraud detection

About SentiLink

SentiLink provides solutions to help financial institutions prevent identity fraud. Their main product uses machine learning models to detect fraudulent activities during the application process. By analyzing data and reviewing cases with a team of risk analysts, SentiLink offers insights that help clients make informed decisions about approving customers. What sets SentiLink apart from competitors is their ability to adapt their products to various types of fraud and customize them to meet the specific needs of each client. The goal of SentiLink is to enable financial institutions to minimize fraud losses while maintaining a positive customer experience.

San Francisco, CaliforniaHeadquarters

2017Year Founded

$81.7MTotal Funding

SERIES_BCompany Stage

Fintech, AI & Machine Learning, Financial ServicesIndustries

51-200Employees

Benefits

Health Insurance

401(k) Retirement Plan

401(k) Company Match

Unlimited Paid Time Off

Home Office Stipend

Risks

Sophisticated fraud techniques may outpace SentiLink's current detection capabilities.

Dependence on high-quality data could impact fraud detection effectiveness if data quality declines.

Intense competition in the fintech sector may threaten SentiLink's market position.

Differentiation

SentiLink specializes in detecting synthetic identities using proprietary machine learning models.

The company offers customizable solutions that integrate seamlessly with clients' existing systems.

SentiLink's Facets tool provides feature-specific intelligence to enhance fraud detection accuracy.

Upsides

Growing demand for synthetic identity fraud detection boosts SentiLink's market potential.

Partnerships with Scienaptic AI and Persona enhance SentiLink's fraud detection capabilities.

API-based solutions allow SentiLink to offer seamless integration and customization.

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