Data Scientist (AI)

Company Summary

Gresham is a global financial services technology company specialising in enterprise data automation. We help financial institutions ensure that their operational, regulatory and management data is complete, accurate, timely and fully auditable — particularly within complex environments where data is distributed across multiple systems.

Our solutions automate data controls, reconciliations, workflows and exception management, enabling clients to reduce operational risk, strengthen data governance and enhance confidence in reporting across highly regulated environments. Serving both buy-side and sell-side organisations worldwide, Gresham partners with clients to deliver trusted, transparent and resilient data operations.

We are seeking an Associate Director, Data Scientist (AI), to lead the design, development, and deployment of cutting-edge AI and machine learning solutions that enhance Gresham's data automation platform, driving innovation across financial data integrity, reconciliation, and regulatory reporting for global clients.

Job Responsibilities

• Identifying, designing, and implementing scalable data delivery pipelines and automating manual processes. Data cleaning and transformation/manipulation of raw data.
• ETL process design, implementation, maintenance, and documentation for large inter-connected data sets. Create and maintain detailed documentation of workflows.
• Productionize and scale the already written python/pandas code.
• Employ creative techniques for data wrangling tasks, joining multiple datasets together, data exploration to create unique products while working with domain experts.
• Building required infrastructure for optimal data extraction, transformation and loading of data using cloud technologies like AWS.
• Utilize existing database infrastructures and building new DB infrastructures as required.
• Use of data development software (ETL packages) and programming languages and tools (usually SQL and Python) to develop tools to extract, transform and load data, as well as to document the creation of these tools.
• Identifying, assembling, and enriching a wide range of structured and unstructured data to support new financial data sets and analysis.

Job Requirements

• 8-13 years of experience in data manipulation/engineer role with an engineering background.
• Strong understanding of data, including how to interpret it, perform Exploratory Data Analysis (EDA) if required, and extract meaningful insights from it. Highlight data issues and inconsistencies, if any.
• Expertise in Python and data manipulation libraries like Pandas, NumPy is a must.
• Ability to refactor, optimize and productionize the already written POC code.
• Proven experience with SQL databases like Oracle DB/SQL Server/MySQL/Snowflake.
• Proven experience with AWS (Glue, Athena, EC2, S3, Lambda, RDS)
• Working knowledge of Iceberg / delta lake tables
• Experience working with CI/CD, Infrastructure-as-Code, and other automation tools.
• Familiarity with DevOps tool
• Familiar with techniques to manage large datasets, including partitioning, indexes as well as data mining.
• Excellent communication skills as you will need to discuss technical principles and business processes in simple language to people at all levels.
• Be able to build relationships with global colleagues working remotely.
• Enthusiasm for learning, trying new things, sharing knowledge, and developing skills in others.
• Being independent and proactive to find information and raise questions.
• Data acquisition skills would be advantageous.

Equal Opportunities Statement

At Gresham, we are committed to building a diverse and inclusive workforce that reflects the communities we serve. We actively encourage applications from individuals of all backgrounds and are dedicated to providing a workplace where everyone feels valued, respected and supported.

We make employment decisions based on merit, skills and potential, and do not discriminate based on any protected characteristic. We are also committed to making reasonable adjustments throughout the recruitment process and employment lifecycle.