Aczxenius Avro

Data Science & Business Analytics Professional
Chicago, US.

About

Highly accomplished Data Science and Business Analytics professional with over 14 years of experience at leading firms like Meta and Accenture. Expertly translates complex business problems into high-impact Machine Learning and Data Mining solutions, delivering actionable insights and driving strategic decision-making across diverse international markets.

Work

Accenture
|

Data Science Consultant

Chicago, IL, US

Summary

Leads cross-functional initiatives at Meta, designing and implementing advanced data pipelines and machine learning models to optimize marketing experiments and campaign performance for US and international markets.

Highlights

Spearheaded the design and execution of marketing experiments and Ad campaigns for Meta, collaborating closely with cross-functional marketing teams to drive strategic decision-making.

Developed and deployed robust Machine Learning models for propensity targeting across US and international markets, enhancing campaign effectiveness.

Engineered resilient Data Engineering pipelines to support on-platform and off-platform campaign measurement, utilizing randomized control trials (RCT) with synthetic lookalike methodologies.

Compass Group USA
|

Data Scientist

Charlotte, NC, US

Summary

Leveraged advanced analytical techniques including Market Basket Analysis, Time Series Forecasting, and Anomaly Detection to provide actionable insights for diverse business units.

Highlights

Developed a robust Spark, Python, and R script for quarterly Market Basket Analysis, processing point-of-sale transactions from the data warehouse and loading results into Data Mart for ≈2.2K business units.

Designed and deployed an interactive Shiny dashboard for Time Series Forecasting (ARIMAX/Prophet), visualizing trends, seasonality, and providing 365-day sales forecasts.

Created a Python script for Anomaly Detection, automatically flagging anomalous transactions and updating the data mart, improving data quality and integrity.

Executed Cluster and Discriminant Analysis (Python/R) using Hierarchical and K-Means clustering, identifying relevant clusters for business profile segmentation and delivering key insights to stakeholders.

UNCC, Data Science Initiative
|

Graduate Teaching Assistant

Charlotte, NC, US

Summary

Supported over 50 graduate students in Visual Analytics, providing guidance on Tableau, D3.js, and R Shiny dashboards.

Highlights

Provided primary technical and conceptual support to over 50 graduate students in the Visual Analytics course, focusing on Tableau, D3.js, and R Shiny dashboard development.

Accenture
|

Senior Data Analyst

Amsterdam, North Holland, Netherlands

Summary

Analyzed financial instruments and led ETL development for a major insurance and asset management client, optimizing data warehousing and reporting processes across Netherlands and India.

Highlights

Conducted quantitative analysis and statistical modeling using R to assess performance of funds and diverse financial instruments for a leading insurance and asset management client organizations in the Netherlands.

Collaborated with data architects and business stakeholders to design and develop OLAP Cubes using SSAS tabular model, facilitating factsheets and sales reports, and implementing SSRS reports with Data Analytic Expressions.

Served as a Senior ETL Developer, utilizing Informatica PowerCenter to design, develop, and maintain ETL workflows for data warehouses, data marts, and Hadoop ecosystems.

Automated daily business reports using UNIX shell scripting, SQL, and PL/SQL, reducing manual effort by 3 FTE and significantly improving performance of databases and ETL tasks.

Education

University of North Carolina at Charlotte
Charlotte, NC, United States of America

Masters

Data Science and Business Analytics

Grade: 3.91/4.0

University of Pune
Pune, Maharashtra, India

Bachelor

Computer Engineering

Skills

Languages

Python, SQL, R, Linux Shell Scripting, Java.

Machine Learning

Classification, Regression, Clustering, Association Rule Mining, Anomaly Detection Algorithms, Dimensionality Reduction, Time Series Analysis, Ensemble Models, Hyperparameter Tuning, Regularization, Topic Modelling (LDA), Word2Vec, Sentiment Analysis.

Statistical Modeling

Hypothesis Testing (t-test, chi square test etc.), ANOVA, Design of Experiments.

Platforms/Libraries/Tools

scikit-learn, H2O, R (Caret), Informatica PowerCenter.

Data Visualization

Tableau, R(Shiny), Matplotlib, Seaborn.

Databases and Big Data

Presto, Spark (PySpark), Hive, Oracle, Microsoft SQL Server, MySQL, Teradata, Hadoop.