Amanpreet Kaur

Business Development Executive

Gurugram, Haryana, India13 yrs experience

Highly StableAI ML Practitioner

Key Highlights

9 years of experience in technical and project management.
Expertise in predictive modeling and machine learning.
Proficient in data visualization using Power BI and Tableau.

Stackforce AI infers this person is a data-driven professional specializing in predictive analytics and machine learning within the SaaS industry.

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Skills

Core Skills

Predictive ModelingStatistical ModelingData VisualizationData MigrationCloud Computing

Other Skills

AWSAmazon EC2Amazon S3Amazon Web Services (AWS)Base SASBusiness AnalyticsCluster AnalysisData AnalysisData AnalyticsData MiningData ReportingData ScienceLinear RegressionLogistic RegressionMachine Learning

About

• A performance driven professional offering 9 years of rich experience in technical development, people management, project management, onshore and offshore delivery • Domain knowledge of Automotive market & Pharmaceutical • Extensive knowledge on Predictive Modeling and Machine Learning Algorithms using Python and SAS • Proficient in Data Visualization Techniques - Power BI and Tableau • Experience in managing a Team of 6-8 members • Successfully completed the SAS Base Programming for SAS 9 offered by SAS Institute.

Experience

Eli lilly services india private ltd

Manager

Jul 2021 – Present · 4 yrs 8 mos

Predictive ModelingStatistical Modeling

Ihs markit | technology

Senior Data Analyst

Dec 2016 – Jul 2021 · 4 yrs 7 mos · Gurgaon, India

Executing standard and custom models to predict the likelihood of a household buying a certain brand or segment
Forming models such as vehicle budget category predictors, garage predictors & return to market Monitoring cyclical scoring process for the predicted models and sales-match/performance array Developing interactive tableau dashboards for clients to assess the performance of their competition in the market based on sales/demographic/registration/dealer data
Bringing out better variants of the current modelling process by using second pass and division based modelling approach
Using Logistic Regression in SAS Enterprise Miner after comparing its results with Decision trees, Neural Networks and Random Forest (both generic and HP)
Migrating all SAS projects, modules, programs to AWS compatible Python scripts and scoring jobs, sampling process from SAS to Python
Automating the input file transfer from SAS server directories to S3 storage buckets in AWS, release of output files from S3 buckets to client specific server locations using Hadoop
Managing time-based schedulers for jobs using CRON in AWS
Performing rigorous quality checks on the 4-step modelling process: sampling, modelling, scoring and sales-match
Communicating with client on regular basis to help them with their custom requests
TECHNICAL SKILLS
SAS: Base SAS Certified, SAS procedures and Data Management, Advance SAS & Macros
Managed AWS EC2 instances, S3 Data Storage Fundamentals, Gitlab, Jupyter Notebook, Python Scripting, SQL
Created interactive Tableau dashboards
ML Modelling: Regression, Decision Trees, Neural Networks, Random Forest
Data Sampling, Scoring and Validation.
Likelihood Ratios, Multivariate and Cluster Analysis for Biochemical Parameters Data Manual and Automation Testing
MS Office, Windows and UNIX operating system
Worked with client specific DT Tool (Data Transformation) to perform Data Cleaning & Data Mapping

Predictive ModelingStatistical ModelingLogistic RegressionData VisualizationTableauSAS+3

Tata consultancy services

2 roles

System Engineer

Mar 2013 – Nov 2016 · 3 yrs 8 mos

Clinical SAS Programmer

System Engineer

Mar 2013 – Nov 2016 · 3 yrs 8 mos

Transformed data from one standard to another using client specific tools & SAS macros Generated report and analyzed data for coherency and consistency
Automated the processes to improve efficiency and minimize the overheads involved and extracted data using SAS macros
Executed quality check on vendor data and communicated with clients about the requirements and discrepancies related to process & data