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SentiLink · 1 week ago

Model Risk Data Scientist

United States

Full-time

Remote

Mid, Senior Level

$140K/yr - $180K/yr

3+ years exp

SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. The Model Risk Data Scientist will build foundational processes for generating model performance metrics and act as a point of contact for Strategic Financial Partners, managing their model governance needs.

Cyber SecurityFraud DetectionIdentity ManagementInformation TechnologyNetwork Security

No H1B

Responsibilities

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

Qualification

PythonData analysisModel governanceSQLGitHubAnalytical skillsDomain expertiseProblem-solvingCommunication skillsFast-paced environment

Required

Bachelor's, Master's, or PhD in Data Science, Statistics, Computer Science, or a related field

3 years of work experience in a related technical field, or 5-7 years relevant applied academic experience

Proven experience in data analysis, modeling, and performance evaluation

Strong proficiency in Python, and specifically data analysis libraries (Pandas, Numpy), Data Visualization (Python matplotlib Plots, Excel Plots / BI tools), and SQL

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 model risk analysis and model governance work

Ability to thrive in a fast paced environment characterized by the need to solve extremely varied, high impact, open ended problems

Candidates must be legally authorized to work in the United States and must live in the United States

Preferred

Proven experience in assessing the quality, stability, performance and behavior of production grade ML models, ideally from the perspective of model governance, fair lending or economic risk is highly preferred

Familiarity with fraud detection preferred

Experience with GitHub