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Senior Data Scientist - Document VerificationPosition OverviewWe are seeking a highly technical and analytical Senior Data Scientist to develop and improve machine learning solutions that support product performance, risk detection, customer experience, and operational efficiency.This role combines machine learning model development, data analysis, model evaluation, experimentation, and automation. The Senior Data Scientist will work closely with Product, Engineering, Operations, and other Data Science teams to develop production-ready models, generate actionable insights, and build scalable tools and frameworks that support data-driven decision-making.The ideal candidate has strong technical expertise in machine learning, statistics, Python, and SQL, along with experience developing and evaluating models in a production environment.Key ResponsibilitiesMachine Learning &amp; Model Development<ul style="margin:0px;padding-left:40px;">
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Design, develop, test, and improve machine learning models for risk detection, verification, classification, image analysis, and other business applications.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Research and evaluate new features, modeling techniques, algorithms, and approaches to improve model performance.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Develop scalable and production-ready machine learning solutions.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Partner with Engineering teams to deploy, monitor, and continuously improve production models.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Analyze model performance and identify opportunities for optimization and enhancement.</li>
</ul>Data Analytics &amp; Model Evaluation<ul style="margin:0px;padding-left:40px;">
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Analyze product performance, customer behavior, operational trends, and emerging risks to identify actionable insights.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Design and conduct model evaluations using both offline and production datasets.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Measure model performance using appropriate statistical and machine learning metrics, including precision, recall, false acceptance rates, and false rejection rates.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Assess the business impact of model changes and provide recommendations based on quantitative analysis.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Develop and monitor KPIs and dashboards to track model health, product performance, and operational metrics.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Identify trends, anomalies, and emerging issues through data analysis.</li>
</ul>Experimentation, Tooling &amp; Automation<ul style="margin:0px;padding-left:40px;">
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Build tools and automated workflows to support model evaluation, performance monitoring, data analysis, and operational investigations.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Develop self-service analytics and experimentation frameworks that enable teams to make data-driven decisions.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Improve data and analytics infrastructure supporting machine learning development and monitoring.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Automate repetitive analytical and model evaluation processes to improve efficiency and scalability.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Support the development of frameworks for experimentation, testing, and model validation.</li>
</ul>Cross-Functional Collaboration<ul style="margin:0px;padding-left:40px;">
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Partner with Product, Engineering, Operations, and other technical teams to translate business challenges into data-driven solutions.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Collaborate with stakeholders to define analytical requirements, success metrics, and evaluation methodologies.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Communicate complex technical findings and recommendations clearly to both technical and non-technical audiences.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Provide data-driven insights that help influence product development and modeling decisions.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Contribute to the development of best practices for machine learning, analytics, experimentation, and model evaluation.</li>
</ul>Required Qualifications<ul style="margin:0px;padding-left:40px;">
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Master's or Ph.D. degree in Computer Science, Statistics, Data Science, Mathematics, Engineering, or a related quantitative field, or equivalent professional experience.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">
5+ years of experience in data science, machine learning, fraud/risk analytics, product analytics, or a related field.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Proven experience developing, evaluating, and improving production machine learning models.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Advanced proficiency in Python and SQL.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Strong understanding of machine learning methodologies, statistical analysis, experimentation, and model evaluation.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Experience working with large-scale data and cloud-based data platforms.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Experience with technologies such as Databricks, Apache Spark, AWS SageMaker, or comparable platforms.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Strong analytical and problem-solving skills with the ability to translate complex data into actionable business insights.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Excellent written and verbal communication skills.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Ability to work independently while collaborating effectively with cross-functional teams.</li>
</ul>Preferred Qualifications<ul style="margin:0px;padding-left:40px;">
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Experience with computer vision, deep learning, or transformer-based models.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Experience developing models for fraud detection, identity verification, risk management, security, or related applications.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Experience designing and analyzing A/B tests, online experiments, and statistical evaluations.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Experience defining product KPIs and developing dashboards to monitor product performance and customer behavior.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Experience building automated machine learning evaluation, monitoring, or experimentation frameworks.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Familiarity with modern ML deployment, monitoring, and MLOps practices.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Experience working with large-scale production datasets and distributed computing environments.</li>
</ul>

Senior Data Scientist - Document Verification

Position Overview

We are seeking a highly technical and analytical Senior Data
Scientist to develop and improve machine learning solutions that
support product performance, risk detection, customer experience,
and operational efficiency.

This role combines machine learning model development, data
analysis, model evaluation, experimentation, and automation. The
Senior Data Scientist will work closely with Product,
Engineering, Operations, and other Data Science teams to develop
production-ready models, generate actionable insights, and build
scalable tools and frameworks that support data-driven
decision-making.

The ideal candidate has strong technical expertise in machine
learning, statistics, Python, and SQL, along with experience
developing and evaluating models in a production environment.

Key Responsibilities

Machine Learning & Model Development

* Design, develop, test, and improve machine learning models for
risk detection, verification, classification, image analysis, and
other business applications.
* Research and evaluate new features, modeling techniques,
algorithms, and approaches to improve model performance.
* Develop scalable and production-ready machine learning
solutions.
* Partner with Engineering teams to deploy, monitor, and
continuously improve production models.
* Analyze model performance and identify opportunities for
optimization and enhancement.
Data Analytics & Model Evaluation

* Analyze product performance, customer behavior, operational
trends, and emerging risks to identify actionable insights.
* Design and conduct model evaluations using both offline and
production datasets.
* Measure model performance using appropriate statistical and
machine learning metrics, including precision, recall, false
acceptance rates, and false rejection rates.
* Assess the business impact of model changes and provide
recommendations based on quantitative analysis.
* Develop and monitor KPIs and dashboards to track model health,
product performance, and operational metrics.
* Identify trends, anomalies, and emerging issues through data
analysis.
Experimentation, Tooling & Automation

* Build tools and automated workflows to support model
evaluation, performance monitoring, data analysis, and
operational investigations.
* Develop self-service analytics and experimentation frameworks
that enable teams to make data-driven decisions.
* Improve data and analytics infrastructure supporting machine
learning development and monitoring.
* Automate repetitive analytical and model evaluation processes
to improve efficiency and scalability.
* Support the development of frameworks for experimentation,
testing, and model validation.
Cross-Functional Collaboration

* Partner with Product, Engineering, Operations, and other
technical teams to translate business challenges into data-driven
solutions.
* Collaborate with stakeholders to define analytical
requirements, success metrics, and evaluation methodologies.
* Communicate complex technical findings and recommendations
clearly to both technical and non-technical audiences.
* Provide data-driven insights that help influence product
development and modeling decisions.
* Contribute to the development of best practices for machine
learning, analytics, experimentation, and model evaluation.
Required Qualifications

* Master's or Ph.D. degree in Computer Science, Statistics, Data
Science, Mathematics, Engineering, or a related quantitative
field, or equivalent professional experience.
* 5+ years of experience in data science, machine learning,
fraud/risk analytics, product analytics, or a related field.
* Proven experience developing, evaluating, and improving
production machine learning models.
* Advanced proficiency in Python and SQL.
* Strong understanding of machine learning methodologies,
statistical analysis, experimentation, and model evaluation.
* Experience working with large-scale data and cloud-based data
platforms.
* Experience with technologies such as Databricks, Apache Spark,
AWS SageMaker, or comparable platforms.
* Strong analytical and problem-solving skills with the ability
to translate complex data into actionable business insights.
* Excellent written and verbal communication skills.
* Ability to work independently while collaborating effectively
with cross-functional teams.
Preferred Qualifications

* Experience with computer vision, deep learning, or
transformer-based models.
* Experience developing models for fraud detection, identity
verification, risk management, security, or related applications.
* Experience designing and analyzing A/B tests, online
experiments, and statistical evaluations.
* Experience defining product KPIs and developing dashboards to
monitor product performance and customer behavior.
* Experience building automated machine learning evaluation,
monitoring, or experimentation frameworks.
* Familiarity with modern ML deployment, monitoring, and MLOps
practices.
* Experience working with large-scale production datasets and
distributed computing environments.

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Joe Watts

Active - OPEN

$245K - Senior Data Scientist, Document Verification, JR1223

$245K - Senior Data Scientist, Document Verification, JR1223

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