Data Scientist II

Zeta is a Next-Gen Banking Tech company that empowers banks and fintechs to launch banking products for the future. It was founded by Bhavin Turakhia and Ramki Gaddipati in 2015.
Our flagship processing platform - Zeta Tachyon - is the industry’s first modern, cloud-native, and fully API-enabled stack that brings together issuance, processing, lending, core banking, fraud & risk, and many more capabilities as a single-vendor stack. 15M+ cards have been issued on our platform globally.
Zeta is actively working with the largest Banks and Fintechs in multiple global markets transforming customer experience for multi-million card portfolios.
Zeta has over 1700+ employees - with over 70% roles in R&D - across locations in the US, EMEA, and Asia. We raised $280 million at a $1.5 billion valuation from Softbank, Mastercard, and other investors in 2021.

The Role

• This role provides an exciting opportunity to be at the forefront of AI innovation, contributing to the development and implementation of solutions that push the boundaries of technology.
• If you are passionate about AI, thrive in a collaborative environment, and enjoy driving impactful projects, this position offers a platform for creativity and professional growth. Join us in shaping the future of AI applications

Responsibilities:

• Integration: Collaborate with software engineers to deploy and integrate data models into production systems, ensuring scalability, reliability, and efficiency.
• Metrics Identification: Identify key business metrics, offering insights that inform decision-making processes and recommending product features when necessary.
• Concept Development and Design: Collaborate with cross-functional teams to brainstorm and refine ideas for AI-powered solutions and various NLP/ML use cases. Translate business requirements into technical specifications for models and algorithms. Design and develop innovative solutions that address specific business challenges and enhance user experience.
• Model Development and Optimization: Develop and implement machine learning models using Python, R, or other relevant programming languages. Employ deep learning techniques and algorithms to extract meaningful insights from large datasets. Continuously improve and optimize models to achieve high accuracy and performance.
• Exploratory Data Analysis and Insights: Conduct exploratory data analysis to uncover patterns, trends, and hidden relationships within data. Utilize statistical and data mining techniques to extract valuable insights from unstructured data. Generate actionable recommendations and insights for future product development and feature enhancements.
• Rapid Prototyping and Deployment: Quickly prototype AI solutions to test and validate their effectiveness. Collaborate with software engineers to seamlessly integrate AI models into production systems. Ensure the scalability, reliability, and efficiency of deployed AI solutions.
• Communication and Collaboration: Effectively communicate technical concepts and findings to non-technical stakeholders. Create clear and comprehensive documentation to capture project details, methodologies, and results. Collaborate with software engineers, product managers, and operations teams to bring AI solutions to life.
• Business Impact and Metrics: Identify key business metrics that can be positively impacted by AI solutions. Track and monitor the performance of AI models on relevant business metrics. Recommend product features and enhancements based on data-driven insights and AI-generated recommendations.

Skills

• Quantitative and Problem-Solving Skills: Strong quantitative and problem-solving skills
• NLP and Data Science Libraries: Solid understanding of NLP and knowledge of essential data science libraries, including Pandas, Numpy, Scipy, and Scikit-Learn
• Python Programming: A good hands-on experience with Python used in data analysis and model building
• Distributed Computing Experience: Experience with Hadoop, Spark, or other distributed computing systems for large-scale training
• Machine Learning Techniques: Strong understanding of supervised (decision trees, random forests, boosting, etc.) and unsupervised ML techniques

Experience and Qualifications

• Master's or Bachelor's degree in Machine Learning/Data Science, Applied Statistics, Mathematics, or Engineering
• Minimum 2+ years of relevant experience with a proven track record of developing ML solutions.

Life At Zeta
At Zeta, we want you to grow to be the best version of yourself by unlocking the great potential that lies within you. This is why our core philosophy is ‘People Must Grow.’ We recognize your aspirations; act as enablers by bringing you the right opportunities, and let you grow as you chase disruptive goals. 
#LifeAtZeta is adventurous and exhilarating at the same time. You get to work with some of the best minds in the industry and experience a culture that values the diversity of thoughts. If you want to push boundaries, learn continuously and grow to be the best version of yourself,  Zeta is the place to be!  Explore the life at zeta 
Zeta is an equal opportunity employer.  At Zeta, we are committed to equal employment opportunities regardless of job history, disability, gender identity, religion, race, marital/parental status, or another special status. We are proud to be an equitable workplace that welcomes individuals from all walks of life if they fit the roles and responsibilities.