Job Title
Data Scientist – RM-MIS
Role Overview
The RM-MIS team at 360 ONE Wealth operates at the intersection of data, technology, and client advisory, forming the analytical backbone for Relationship Managers serving ultra-high-net-worth clients.
This role is designed for a seasoned Data Science professional who will lead advanced analytics initiatives within the RM-MIS function. The individual will leverage data to generate investment insights, enhance client experience, and build scalable data-driven solutions. Working closely with senior leadership, investment teams, and technology stakeholders, the role requires translating complex datasets into clear, actionable intelligence that enables faster and more informed decision-making.
Key Responsibilities
1. Analytics & Modelling
- Design and maintain MIS dashboards and performance reports covering AUM flows, revenue, RM productivity, and client activity
- Build granular client-level analytics on wallet share, asset allocation, product penetration, and engagement trends
- Analyse historical transaction and portfolio data to identify investment behaviour patterns and product adoption cycles
- Track and standardise key business KPIs including AUM, revenue yield, SIP/STP flows, and HNI/UHNI metrics
- Enable AI-powered natural language querying for MIS dashboards to drive self-serve analytics
2. Data Science & AI
- Develop client segmentation and profiling models using clustering techniques
- Build recommendation engines for cross-sell opportunities and portfolio rebalancing
- Create wallet share estimation models to identify untapped revenue potential
- Enhance predictive models using advanced techniques such as ensemble learning, gradient boosting, and deep learning
- Integrate generative AI use cases including automated MIS commentary and AI-generated portfolio summaries
3. Data Engineering & Automation
- Automate MIS reporting workflows, reducing dependency on manual processes
- Ensure data quality, governance, and consistency across RM-MIS datasets
4. Business Partnership & Strategy
- Partner with Relationship Managers, Business Heads, and Technology teams to deliver data-driven solutions
- Translate business problems into structured analytical frameworks and communicate insights effectively
- Support strategic planning, business reviews, and leadership presentations through deep-dive analysis
- Define and drive the RM-MIS data strategy aligned with business objectives
- Collaborate with investment teams to generate quantitative insights and identify alpha opportunities
- Lead deployment of analytical models into business systems in partnership with technology teams
- Mentor and lead a team of data scientists and analysts
Skills & Attributes
- Strong analytical and problem-solving capabilities with a deep understanding of statistics and predictive modelling
- Proficiency in Python and SQL, along with data visualisation and analytics tools (e.g., Power BI, Tableau)
- Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow)
- Strong business acumen with the ability to link data insights to revenue and client outcomes
- Excellent stakeholder management and communication skills, with the ability to engage non-technical audiences
- Leadership capabilities with experience managing teams and cross-functional projects
- Ability to operate in a fast-paced, high-stakes environment with a focus on accuracy and timeliness
- Strategic mindset with the ability to bridge business, investment, and technology domains
Qualification & Experience
- 10–12 years of experience in Data Science, Analytics, or MIS roles, preferably within financial services, wealth management, or fintech
- MBA from a Tier-1/Tier-2 institute with a strong quantitative undergraduate background (Engineering, Statistics, Economics, or related field)
- Experience working with portfolio data, AUM metrics, or financial transaction datasets is preferred
- Exposure to cloud platforms (AWS, Azure, GCP) and big data ecosystems is an advantage
- Familiarity with NLP, AI applications, or data-driven investment strategies is desirable
