Shashank Dhall
Director of Data Analytics @Metro Supply Chain
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WORK HISTORY
Director of Data Analytics @Metro Supply Chain
Mississauga, ON, CA
EDUCATION
St. Mark's Senior Secondary Public School
Science Non-Medical, Engineering Science
Kurukshetra University
Bachelor of Technology (BTech), Mechanical Engineering
The ICFAI University, Dehradun
Master of Business Administration (MBA), Marketing & IT
SKILLS
ABOUT SHASHANK DHALL
Experienced, dedicated and a data-driven professional with excellent statistical knowledge and a passion for continuous learning and enhancing my data science/ data analytics skills. Driven by the ability to turn data into actionable insights, my focus has been to improve organizational processes by supporting cross-functional strategic initiatives, specifically through different data science and machine learning techniques.I love being a storyteller, and hence, data visualization and presentation are innate skills that I have been able to hone (and continue to) during my professional journey so far.Analytics-as-a-Service: Labor rate predictive model, Competitive intelligence, Supply market analytics, Cost modeling, Spend reporting and analytics, Bid analytics, Payment terms analytics, Unit Price Variance (UPV) Analytics, Supplier scorecards, Financial reporting and analytics, Category intelligence and analytics, Go-to-market Intelligence.End-to-end analytics workflow design and development: Develop ETL processes using Azure cloud solutions; data processing using Azure Databricks; and data ingestion pipelines and orchestration using Azure Data Factory; maintaining and documenting data workflows and data automation rules; and front-end reporting through dashboard development.Key skills:• Data Visualizations: Tableau, SAP Lumira, Excel PowerView, Microsoft Power BI - PowerPivot• Data Analytics and Programming: Base SAS, R, Python, VBA Macros• Database: MS Access, SQL• Data Analysis and Modeling• Data Wrangling & Transformation: Alteryx, Python (Pandas/ Numpy)• Python libraries: Numpy, Pandas, Scikit Learn, Seaborn, MatplotlibML Techniques: Linear and Logistics Regression, Time Series Forecasting, K Means Clustering, Principal Component Analysis (PCA), Decision Trees & Random Forest
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