Cabot Financial

Working on several high-profile projects using cutting edge BigData technologies such as Spark Databricks, Azure, Delta Lake, MLFlow using agile methodology to produce highly sophisticated ML models while working closely with Strategy & Insights and Operations team to operationalise.

Working on developing a predictive algorithm which includes a combination of four models (Regression and XGBoost) that could help rank 10 million customers based on their Net Plan Value prediction using 15 years survival curves and cash flow forecast.

Worked on Customer Classification project clustering customers based on their demographics, financials and life-style/socio-economic, with external data sourced from bureau (Experian) and Doorda (aggregated data from 1500 official sources on housing, census, businesses etc.). Cumulative annual gain is expected to be at-least £1.2m.

Worked on an advanced analytics project creating new triggers from bureau data with over 400 variables and 900 million rows for each Experian and TransUnion. These triggers would indicate change in customer’s situation to help devise appropriate strategies to be actioned upon.

Worked on NLP (BERT with GradientBoosting) project that could identify millions of pounds of unrealised benefits hidden in millions of rows of call-agents free text notes.

Researching new technologies, tools and methodology to improve productivity & efficiency. Implementing Large Language Models to assist in coding and other downstream tasks (summarisation, classification). https://shorturl.at/qAQ38

Senior Data Scientist

South London and Maudsley NHS Foundation Trust

Worked on exogenous multivariate TimeSeries model to forecast A&E admissions and hospital readmissions. Helped identify casual factors to develop local Population Health Management programmes to improve patient's access, experience and outcomes with health services. Utilized Azure ML Studio, DevOps, SQL and PowerBI for end-to-end project delivery which helped in proactively planning for demand and capacity allowing for effective resource allocation and optimization.

Data Scientist

Independent

Worked on several Digital Transformation and Predictive Analytics projects. Worked on Machine Learning projects (NLP) on case management, capacity & demand modelling, market size modelling, inorganic/organic growth strategy, product analytics, market research, due-diligence.

Clients: LEK consulting, Generali Insurance, JLT Employee Benefits, April Intl (France), MSH Intl (France), NHS, Meridian Productivity, ISS

Consultant (Data Science, Management Consulting)

GLG (Gerson Lehrman Group)

Expert Network Council Member

McGRIGOR group

Worked on market research, modelling, organic & in-organic growth strategy and due diligence for several leading insurance clients (AXA, Bupa, Global Benefits Group (GBG-USA))

Senior Business Advisory Consultant

Accenture

Worked on claims analytics, portfolio analysis and population health management (PHM)/Corporate wellness projects for Fortune 250 clients

Senior Consultant, Accenture Strategy

GE Healthcare

Designed a multi-dimensional bespoke tool for strategic business planning

Strategic Programme Management Consultant

UPMC

Worked on large structured and unstructured data (Electronic Medical Records) for business intelligence reporting, providing strategic and operational insights and designing productivity improvement strategies

Senior Analyst

Zeeik, a division of ComPePrice LLC

Advisor, Business and Technology Development

ComPePrice LLC

Data Scientist with Management consulting skills and strong experience in business analytics, strategy and operations. Entrepreneur experience with two start-ups in the USA and UK. Now applying data science and business consulting skills to advise on strategy and decision-making.

Core Areas of Expertise: GenerativeAI, Data Science, Predictive Modelling, Machine Learning, Business Analysis, Stakeholder Management, Operations & Process Improvement, Due-Diligence, Financial Modelling, Healthcare IT, BigData (Databricks, PySpark, Azure).

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