Partner with the Business Unit Lead to identify gaps in decisioning performance and implement solutions.
Build production machine learning models to identify fraud in collaboration with other data scientists.
Communicate complex ideas to a variety of audiences, from Customer Success to Sales.
Signifyd helps merchants confidently grow their businesses by building trusted relationships with customers. Their advanced technology creates frictionless shopping experiences, and they are trusted by thousands of merchants across over 100 countries.
Own fraud detection models end-to-end, from data acquisition to production and monitoring.
Research new fraud vectors and develop products for identity verification and financial risk.
Write production code and present analyses to drive product, risk, and sales decisions.
SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. We are a rapidly growing fintech startup backed by world-class investors, with offices across the US and India.
Own the full model lifecycle from requirements and feature engineering through deployment and monitoring, partnering with ML engineers.
Translate complex fraud patterns into well-framed ML solutions, defining what to model and where ML adds value.
Design feature engineering pipelines, monitor model quality in production, and collaborate across teams to drive fraud strategies.
Extend revolutionizes the post-purchase experience for retailers by providing AI-driven solutions that enhance customer satisfaction and drive revenue growth. Backed by prominent technology investors and headquartered in San Francisco, Extend works with over 1,000 leading merchant partners across industries, fostering a collaborative and supportive culture.
Build and deploy machine learning models for credit and fraud risk management.
Collaborate with engineering to deploy models into production and analyze portfolio performance.
Communicate findings to stakeholders and develop internal tools for data science productivity.
Prosper is a fintech company that offers personal loans and credit cards through a digital marketplace. They have helped over 2 million customers and emphasize a collaborative, inclusive culture with flexible work options.
Evaluate sophisticated machine learning models, traditional quantitative models, and emerging Generative AI applications.
Partner with cross-functional teams to maintain model inventories, risk assessments, and governance materials.
Translate complex technical concepts into clear insights for stakeholders and support regulatory readiness.
A growing technology-driven banking environment focused on consumer lending and financial services. The company emphasizes a remote-first culture, cross-functional collaboration, and inclusive workplace practices.
Lead ads fraud detection strategy by defining taxonomies, labels, metrics, and evaluation frameworks.
Analyze large datasets to uncover fraud patterns and translate findings into scalable detection and enforcement pipelines.
Build and maintain statistical, ML, and GenAI models to improve fraud detection, risk identification, and enforcement quality.
Reddit is a community of communities, built on shared interests and authentic conversations. With 100,000+ active communities and approximately 130 million daily active users, it is one of the internet's largest sources of information, fostering an open and inclusive culture.
Develop and optimize fraud prevention strategies using advanced analytics and machine learning.
Monitor fraud trends and client portfolios to identify emerging threats and recommend mitigation measures.
Serve as a fraud risk expert, providing analytical findings and recommendations to stakeholders.
The partner company specializes in fraud prevention and risk analytics for financial institutions, operating in a fast-paced payments environment. They are a remote-first organization with a focus on collaboration and work-life balance.
Lead and mentor a team of quantitative professionals while personally executing rigorous validations of machine learning models for underwriting and credit risk.
Evaluate conceptual soundness, data integrity, and performance stability through comprehensive testing, in-depth reviews, and continuous monitoring.
Collaborate with cross-functional stakeholders to enhance the enterprise-wide Model Risk Management framework and ensure compliance with internal and regulatory standards.
Affirm is a financial technology company that provides buy now, pay later services without hidden fees or compounding interest. It is a publicly traded, remote-first company with a large workforce and a culture focused on innovation, risk management, and putting people first.
Develop and maintain fraud detection models through the full model development lifecycle, from data acquisition to monitoring.
Research new types of fraud and build products around identity verification using Python and AWS infrastructure.
Write production-ready code and present analyses to inform data acquisition, product development, and marketing efforts.
SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. Backed by world-class investors including Craft Ventures and Andreessen Horowitz, the company has grown rapidly, verifying hundreds of millions of identities and earning recognition from Forbes and CNBC.
Lead applied AI projects from concept to impact, building and deploying ML/GenAI solutions across product, engineering, and security teams.
Act as an internal AI consultant, scoping problems, evaluating approaches, and advising on best practices for generative technologies.
Design experiments, build models for anomaly detection and fraud analysis, and bridge research to production via scalable APIs and tools.
Sonatype is a software supply chain management company that invented componentized software development and pioneered the category. Trusted by over 2,000 organizations, including 70% of the Fortune 100, and 15 million developers, the company fosters innovation, AI/ML adoption, and an inclusive culture.
Build monitoring infrastructure for production ML and GenAI models.
Define and track model health metrics including accuracy, drift, and output quality.
Partner with data scientists and ML engineers to integrate monitoring into deployment lifecycle.
Liberty Mutual is a global insurance company that provides property and casualty insurance. The company values inclusion, professional development, and employee well-being, offering comprehensive benefits and workplace flexibility.
Directly manage a team of applied ML scientists, coaching them through model development and technical decision making.
Own execution for your area, including priorities, delivery, and results, while remaining hands-on with code review and production systems.
Partner with senior leadership, Product, Engineering, and Risk to prioritize work and deliver impactful ML solutions.
SentiLink provides innovative identity and risk solutions, building the future of identity verification in the United States. They are a fast-growing company backed by top investors, with offices across the US and India, and have earned recognition from major media outlets.
Provide technical ownership for applied AI and data science initiatives across Sonatype, helping define approaches, architecture, priorities, and standards.
Lead complex AI projects from concept to production—translating ambiguous business and technical problems into measurable experiments and scalable solutions.
Act as a senior internal AI consultant to product, engineering, security, and research teams, helping identify high-value opportunities and advising teams on ML and GenAI approaches.
Sonatype is the software supply chain management company that invented componentized software development and pioneered the software supply chain category. Trusted by more than 2,000 organizations and over 15 million developers, we are committed to constant innovation using AI/ML.
Design, develop and deploy machine learning and statistical models that forecast customer cash flows, credit risk and other business metrics.
Use experimentation and statistical methods to test product, pricing and underwriting changes to improve customer experience.
Monitor models in production, investigate performance issues, and retrain or update models in collaboration with engineering and product teams.
Pipe is a financial technology company that provides a platform for businesses to access capital by selling their future cash flows. The company is fully remote, with a culture of authenticity, humility, and excellence, and offers competitive benefits including flexible vacation and generous parental leave.
Drive innovation across the machine learning ecosystem and architect advanced ML solutions.
Mentor junior ML engineers and lead complex ML initiatives at scale.
Own models in production including deployment, monitoring, drift detection, and retraining.
Xsolla is a global commerce company providing tools and services to help video game developers fund, distribute, market, and monetize their games. Headquartered in Los Angeles, California, Xsolla has helped over 1,500 game developers grow their businesses worldwide.
Architect, test, and deploy LLMs and agents to automate unstructured data investigations and multi-step workflows.
Perform SQL queries and data analyses to optimize gross margins, reduce fraud, and improve network quality.
Collaborate cross-functionally to translate business needs into scalable data products and drive end-to-end ownership.
Twilio is shaping the future of communications, delivering innovative solutions to hundreds of thousands of businesses and empowering millions of developers worldwide. As a remote-first company, we foster a strong culture of connection and global inclusion.
Own the full lifecycle of ML models for credit risk decisions, from feature engineering to production and monitoring.
Design and improve approval amount sensitivity models, credit line optimization, and loss forecasting.
Partner cross-functionally with risk, engineering, finance, and sales to shape both technical infrastructure and business strategy.
Kafene is a fintech company revolutionizing lease-to-own with AI and machine learning. With over $500 million in originations, our 175-person team operates from NYC and globally, fostering a collaborative culture recognized by Built In and Forbes.
Build and maintain trusted product data assets using dbt, Snowflake, and modern analytics infrastructure.
Leverage AI-powered analytics tools to accelerate insight generation and automate repeatable analysis.
Partner closely with Product, Engineering, Design, and Customer Success to influence product strategy through data.
Vanta helps businesses earn and prove trust by enabling continuous security monitoring and compliance. With thousands of customers, Vanta has a kind and talented team focused on building the leading Trust Management Platform.
Design, build, and deploy machine learning models for cybersecurity use cases like threat detection and risk scoring.
Own the full model lifecycle from data preparation to production deployment, working closely with engineering and product teams.
Build preprocessing and feature engineering pipelines, and monitor model performance with continuous improvement.
SpyCloud transforms recaptured darknet data to disrupt cybercrime. With over 250 employees, it is home to cybersecurity experts protecting businesses and consumers from stolen identity data.
Use data, experimentation, and machine learning to solve complex product and business problems at high-growth startups.
Partner with product, engineering, and business leaders to identify high-impact opportunities for data science.
Develop predictive models, design experiments, and translate analyses into clear recommendations for stakeholders.
SignalFire is a venture capital firm that partners with top early-stage startups shaping the future of technology. With a portfolio of over 200 innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS, they are looking to connect with exceptional data scientists who are excited about using data, experimentation, and machine learning to solve complex problems.