Anant Sharma
Data Scientist @Trade Nation
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WORK HISTORY
Data Scientist @Trade Nation
London, GB
Budget Forecasting: Improved annual budget accuracy by developing a data-driven forecasting model using client, revenue, seasonality, and external market data (VIX), adopted for company-wide yearly planning.AML Risk Profiling Application: Enhanced AML compliance by building a Dash app enabling Compliance and Payments teams to monitor, tag, and manage highlighted transactions, high-risk and vulnerable client profiles.AML Risk Detection Pipeline: Strengthened AML Risk Mitigation by developing a machine learning pipeline using unsupervised anomaly detection to generate risk scores and alerts for Payments and Compliance.Client Profitability Prediction: Informed quarterly budgeting and strategy by developing a tree-based model pipeline to forecast client revenue over 3- and 6-month periods by leveraging historical and seasonal client, trades and transactions data.Client Portfolio Segmentation: Boosted retention and personalization by building a machine learning pipeline to segment clients into four profitability groups, optimizing relationship and retention team assignments.Transaction Monitoring Application: Reduced manual investigation/intervention time by designing a near real-time Dash app to monitor transactions with dynamic filtering and alerts, adopted across the Payments, Relationship and Desk teams.Trade Monitoring Application: Enhanced trade oversight by building a scalable Dash app to monitor live trades, adopted across Operations, Relationship and Trading Desk teams.
EDUCATION
Dr. A.P.J. Abdul Kalam Technical University (AKTU), Lucknow
Bachelor of Technology - BTech
University of Glasgow
Master of Science - MSc
ABOUT ANANT SHARMA
I’m a full-stack Data Scientist with a strong foundation in analytics, product thinking, and end-to-end delivery. My work spans the responsibilities typically divided between Data Science, Data Analytics, and Product Analytics. I operate at the intersection of machine learning, stakeholder insight, and business outcomes.At Trade Nation, I joined as the first and only Data Scientist and built the entire data function from the ground up. I have independently delivered machine learning pipelines, forecasting models, anomaly detection systems, near real-time monitoring dashboards, and strategic analytics used across teams including Compliance, Product, Sales, Marketing, and Finance. Each project has been driven by a clear focus on business impact, from reducing fraud risk and improving conversions to supporting executive-level financial planning.My experience includes supervised and unsupervised learning, anomaly detection, segmentation, time series forecasting, and business intelligence reporting, all applied to real business use cases. Some of the key projects I have led include:• An AML Risk Scoring system adopted by Payments and Compliance• A Client Segmentation model that guided account management strategy• A Budget Forecasting system used in quarterly financial planning• A Conversion Scoring model that improved lead prioritisation for Sales• Real-time Dash applications to monitor trades and transactions at scaleI build and automate data pipelines using Python and AWS tools such as Lambda, S3, Redshift, and Athena. I also integrate diverse data sources including PostHog, Google Analytics, Acuity, and internal APIs to power reporting and predictive models. On the analytics side, I have delivered deep dives, cohort and funnel analyses, forecasting, retention and churn analysis, regulatory reporting, and lifetime value modeling.I work hands-on with Python and SQL, and use tools such as Pandas, NumPy, scikit-learn, XGBoost, LightGBM, Dash, Grafana, Metabase, Docker, GitLab, DataGrip, VSCode, and HubSpot. I have delivered tailored dashboards, reports, and data products to more than ten internal teams, always focused on usability, clarity, and adoption.What sets me apart is not just technical expertise but the ability to connect data to business strategy. I work closely with stakeholders, identify the right problems, and deliver tools and insights that lead to real-world decisions and scalable solutions.I am especially drawn to roles where data directly drives product strategy, operational improvement, and business growth.
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