AI Applied Scientist (Machine Learning)- MoneyLion

About Gen
Gen is a global company dedicated to powering Digital Freedom through its trusted consumer brands including Norton, Avast, LifeLock, MoneyLion and more. Our combined heritage is rooted in financial empowerment and cyber safety for the first digital generations, and today we deliver award-winning cybersecurity, online privacy, identity protection and financial wellness solutions to nearly 500 million users in more than 150 countries.

Together, we share a collective passion and vision to protect consumers and help them grow, manage and secure their digital and financial lives. We’re always looking for smart, fearless and high-impact talent who see AI as a teammate – leveraging it to move faster and deliver meaningful results.

When you’re part of Gen, you’ll have the flexibility, tools and support to do your best work and grow your career – from flexible working options and time off to competitive pay, benefits and well-being programs.

At Gen, we are scrappy and relentlessly customer driven. We create room for healthy debate, experimentation and continuous learning, and we seek out people with different experiences, identities and ideas to join our team. You’ll work with people who back each other, respect each other and understand that our differences are a competitive advantage.

If this sounds like you, we’d love you to be part of Gen.

About the Role

We are looking for an Applied AI Scientist (Machine Learning) who is passionate about using data, machine learning, and AI to solve complex problems and create meaningful impact.

This is a hands-on role that combines experimentation, solution development, and technical innovation. You will leverage a range of techniques to develop effective solutions to complex problems, explore emerging technologies and research, and transform ideas into meaningful capabilities that deliver practical impact.

The ideal candidate is curious, analytical, and excited about solving complex problems. You enjoy building, learning, and experimenting with new approaches while maintaining a strong focus on delivering meaningful outcomes.

Key Responsibilities

• Solve complex problems through data, experimentation, and evidence-based approaches.

• Design, build, and improve intelligent solutions and capabilities.

• Build and evolve solutions from concept to production.

• Collaborate with scientists, engineers, and product teams to deliver impactful outcomes.

• Contribute to responsible AI practices, knowledge sharing, and the adoption of effective AI solutions.

• Stay current with emerging technologies, research, and industry developments, and apply relevant innovations where appropriate.

• Contribute to high-quality solutions through experimentation, evaluation, and continuous improvement.
  

About You

• Curious, analytical, and passionate about solving problems using data, machine learning, AI, and emerging technologies.

• Hands-on experience building data-driven applications, analytical solutions, intelligent systems, or AI-powered capabilities.

• Familiarity with machine learning, statistical, analytical, or AI techniques.

• Strong technical judgment, software development, and problem-solving skills.

• Able to independently drive projects from idea to implementation.

• Able to evaluate different approaches and make practical technical decisions.

• Strong communication skills and ability to collaborate effectively with diverse teams.

• Experience developing data-driven applications, algorithms, predictive models, optimization solutions, or similar intelligent capabilities.

• Experience working with complex systems, datasets, or production environments.

• Contributions to open-source projects, technical communities, hackathons, research initiatives, publications, or personal projects.

What’s Next

• HM Screening Call

• Take-Home Assessment

• Interview & discussion of Take-Home Assessment with the Hiring Manager (F2F)

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Gen is an equal opportunity employer, and we’re committed to fair, inclusive practices at every stage of the candidate and employee journey. Employment decisions are based on merit, experience and business needs.