Data Scientist

Role Overview

We are seeking a skilled Data Scientist to design and implement advanced machine learning, statistical, and predictive models addressing complex business challenges across multiple functions. This position involves leveraging cutting-edge AI technologies such as large language models (LLMs), generative AI, and sophisticated analytics to automate workflows, support decision-making, and extract meaningful business insights.

Key Responsibilities

• Architect, build, and assess machine learning and predictive models to resolve diverse business issues.
• Adopt modern AI approaches including deep learning, generative AI, and LLMs to streamline processes and elevate business intelligence capabilities.
• Convert business needs into detailed statistical and analytical solutions that provide tangible value.
• Analyze extensive datasets to discover trends, identify improvements, and optimize operations.
• Collaborate closely with data engineering, IT, and business teams to develop scalable data pipelines and deploy models efficiently into production.
• Assess data integrity and model effectiveness, while responsibly managing model limitations and ensuring ethical AI deployment.
• Effectively communicate findings, insights, and technical details to executives and diverse stakeholders.
• Continuously develop, monitor, and refine predictive models to maintain performance and accuracy.
• Keep abreast of latest AI and machine learning advancements for continuous innovation.
• Work collaboratively across departments to support business intelligence, forecasting, automation, and strategic initiatives.
• Document modeling approaches, assumptions, and procedures comprehensively to maintain transparency and governance.
• Provide support for miscellaneous analytical projects and offer data-driven recommendations to enhance business outcomes.

Qualifications and Experience

• Bachelor’s degree in Mathematics, Data Science, Computer Science, Engineering, Physics, or related quantitative field is mandatory; higher degrees preferred.
• Strong expertise in statistics, predictive algorithms, machine learning, and programming languages such as Python and SQL.
• Proven experience with contemporary AI technologies including deep learning, LLMs, generative AI, and MLOps frameworks.
• Track record of implementing and managing machine learning models in live production environments.
• Solid understanding of cloud platforms and modern data science technologies.
• Capability to assess and optimize model trade-offs involving accuracy, interpretability, speed, and risk under uncertainty.
• Proficiency in translating complex technical subjects to business audiences and working cross-functionally.
• Prior experience in financial services, mortgage lending, or similarly regulated sectors is advantageous.
• Knowledge of model governance, risk management, regulatory compliance is a plus.