Machine Learning Data Scientist

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: Our team is a core contributor to the company’s AI transformation. We apply machine learning and AI to real-world, revenue-impacting problems across a wide range of use cases, including pricing optimization, product recommendations, customer retention, and automation. Our work is deeply embedded in core business systems, with clear ownership, measurable outcomes, and direct business impact. You will have the opportunity to work on high-visibility initiatives and see your solutions deployed at scale. Key Responsibilities: Work end-to-end on machine learning and AI projects, from problem definition and data exploration to modeling, deployment, and impact measurement Conduct experiments (A/B testing, offline evaluation) to validate model performance and business impact Collaborate cross-functionally with product, engineering, and business teams to translate business problems into technical solutions Continuously improve models through iteration, monitoring, and feedback loops Contribute to building data pipelines, feature engineering frameworks, and model infrastructure Communicate insights, results, and recommendations clearly to both technical and non-technical stakeholders About you: Education : Bachelor’s degree required; Master’s or Ph.D. preferred Relevant fields include (but are not limited to): Computer Science, Data Science, Statistics, Mathematics, Engineering, Operations Research, Economics, or related quantitative disciplines Experience : Experience building, deploying, or maintaining machine learning models or data-driven systems is a strong plus Experience with experimentation (A/B testing) and measuring impact is preferred For new graduates, strong project experience or internship experience is highly valued Skills: Strong foundation in machine learning, statistics, and algorithms Proficiency in Python and common ML/data libraries Experience in areas such as deep learning, LLMs, and AI agents is a plus Solid understanding of data processing, feature engineering, and model evaluation Personal Attributes: Strong curiosity and willingness to learn in a fast-evolving AI landscape Ownership mindset with the ability to drive projects end-to-end Passion for applying AI to real-world problems and delivering measurable impact Effective communication skills and ability to work in cross-functional teams For new graduates, we place particular emphasis on learning ability, depth of thinking, problem-solving mindset, and passion for applying AI in production environments, rather than prior industry experience alone. Location:  Mountain V ... (truncated, view full listing at source)