Senior Data Scientist

Your role will involve leading EAMRM data science priorities, collaborating with cross-functional stakeholders, and ensuring alignment with regulatory and governance standards. You will also support innovation in GenAI and platform analytics, leveraging big data cloud platforms and advanced modeling techniques.
You will report to the Director of Data Science and Gen AI.
What you'll do:
Technical Execution-Develop and deploy models using Python or PySpark on big data cloud platforms (e.g., Ascend).Ensure adherence to model risk management and governance processes.
Innovation & Strategy-Support GenAI and platform analytics innovation projects. Craft advanced machine learning analytical solutions and prototypes to extract insights from diverse structured and unstructured data sources. Articulate model processes and outcomes, documenting and presenting findings and performance metrics, and translating complex findings into actionable insights.
Collaborate with Engineering, Research, and Data Science teams in the design and implementation of Machine Learning, Dashboarding, Ad Hoc Analysis and AI applications in a cloud-native big data (AWS) computing platform.
Leverage Gen AI and model development tools to develop and maintain new models. Dissect and document vast datasets, analyzing them to highlight patterns and insights. Develop and assess analytic tools developed internally and externally.
Stay informed about regulatory changes, technological advancements, and model risk management processes and controls to ensure the technology stack meets all compliance requirements. Research, integrate, and test new data assets and software from different sources into Experian's analytic platform.
Gather feedback from internal and external clients to guide new product development, feature prioritization, and product evolution of tools and capabilities.
What you'll bring:
7+ years of experience in AI, data science, or predictive modeling, with a track record for managing complex, hands-on analytical technology, innovation, and client-focused projects. Data science team management experience
Advanced degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field
Statistical modeling proficiency in at least one programming language, with coding skills in Python, and proficiency with distributed computing frameworks (AWS). Experience with large data analysis using Spark (PySpark) and model development using Python or SAS
Expertise with Hadoop and NoSQL related technologies such as Map Reduce, Hive, HBase, MongoDB, Cassandra. Solid understanding of ML algorithms (e.g., XGBoost, GANs, clustering, graph algorithms, hyperparameter tuning)
Experience applying Generative AI-based tools and rapid prototyping of new concepts from ideation through early client success
Proven experience managing analytics or data science teams.

Employment type
Full-time

Work arrangement
Hybrid