We are seeking a Data Scientist who combines strong technical expertise in advanced analytics with a solid understanding of financial markets and investment distribution. This role leverages machine learning, artificial intelligence, and modern data technologies to analyze large volumes of structured and unstructured data, uncover actionable insights, and drive smarter business decisions.
The successful candidate will design predictive models, develop scalable data solutions, and partner closely with data engineering and business teams to translate complex analytics into practical, revenue-driving strategies. Data visualization and dashboard development will be a core component of day-to-day responsibilities.
This is a highly collaborative role requiring both technical depth and strong communication skills to bridge the gap between analytics and business execution.
Design, develop, and deploy predictive models and machine learning algorithms to support business strategy and decision-making.
Use advanced analytical techniques (machine learning, deep learning, AI) to mine and analyze large datasets to identify patterns, trends, and insights.
Develop and test data-driven sales and distribution strategies using statistical modeling and experimentation frameworks.
Partner with data engineers and business analysts to build and optimize data pipelines, analytics tables, and scalable data infrastructure.
Perform large-scale data analysis by combining multiple models, algorithms, and datasets to assess feasibility of AI/ML solutions.
Translate complex analytical findings into clear, actionable recommendations for senior business stakeholders.
Build and maintain dashboards and visualizations to support ongoing performance monitoring and strategic insights.
Evaluate and recommend emerging tools and technologies to enhance data science capabilities.
Anticipate industry and market trends, proactively adapting analytical approaches as needed.
Communicate technical concepts in simple, business-focused language.
Foster strong cross-functional relationships to drive alignment and successful implementation of analytics solutions.
4+ years of relevant experience in data science, analytics, or a related field (or equivalent combination of education and experience).
Strong proficiency in SQL and programming languages such as Python, R, or SAS.
Experience with data visualization tools (e.g., Power BI or similar platforms).
Demonstrated expertise in data analytics, statistical modeling, and machine learning.
Experience building predictive models and working with large, complex datasets.
Strong collaboration skills with a track record of cross-functional teamwork.
Excellent written and verbal communication skills.
Ability to manage ambiguity and operate effectively in dynamic environments.
Proven ability to drive data-informed decision making.
Experience within financial services, investment distribution, or financial markets.
Prior banking or investment industry experience.
CFA designation or advanced degree (Master’s/PhD) in Data Science, Statistics, Mathematics, Finance, Computer Science, or related field.