Solutions Analytics Data Scientist

March 13

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SentiLink

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SentiLink is a company focused on combating identity fraud for financial institutions. By leveraging machine learning models and human expertise, SentiLink provides tailored solutions to stop identity theft at the point of application for various financial services, including deposits, credit, and lending. Their products ensure that customers can access financial services securely while minimizing fraud losses with a flexible and responsive approach to risk management.

51 - 200 employees

Founded 2017

💳 Fintech

🏦 Banking

🔒 Cybersecurity

💰 $70M Series B on 2021-08

📋 Description

• As a Solutions Analytics Data Scientist, you will play a crucial role in enabling current and prospective partners to implement and optimize SentiLink products. • You will conduct data evaluations that demonstrate how SentiLink’s solutions add measurable value to partners' businesses. • This includes analyzing partner data, interpreting key data science metrics, and illustrating product performance. • For existing partners, you will provide ongoing performance assessments, support product evaluations, and deliver custom analyses to help partners understand fraud patterns and their impact on consumers and business operations. • Technologies: Python 3, PostgreSQL, and AWS infrastructure (EC2, S3, RDS, Redshift, etc.) • This is a remote, US-based role. • Conduct comprehensive data evaluations for prospective partners, demonstrating SentiLink's product value through clear data science metrics. • Analyze performance data from current partners to ensure optimal product use and provide actionable recommendations. • Collaborate with cross-functional teams, including Product, Data Science, and Engineering, to enhance product performance and address partner-specific needs. • Deliver ad hoc analyses and reports that provide deep insights into fraud trends, consumer behavior, and partner-specific challenges. • Communicate complex data findings effectively through visualizations, reports, and presentations tailored to both technical and non-technical stakeholders.

🎯 Requirements

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field. • Proven experience in data analysis, modeling, and performance evaluation. • Strong proficiency in data tools and languages such as Python, R, SQL, and data visualization libraries (e.g., Tableau, matplotlib). • Ability to interpret and communicate complex data insights to both technical and business audiences. • Exceptional problem-solving and analytical skills with a focus on actionable results. • Interest in developing deep domain expertise for product-focused work: a background in fraud is not required, but willingness to learn is. • Thrive in a fast paced environment characterized by the need to solve extremely varied, high impact, open ended problems. • Nice to have: Familiarity with fraud detection, risk assessment, or related data-driven business solutions. • Candidates must be legally authorized to work in the United States and must live in the United States.