Machine Learning Data Scientist

SAMIA CHAUDHRY

Email: ***********@*****.*** #:603-***-**** 8S360 Whittington Ct,

Naperville, IL 60540

PROFESSIONAL PROFILE

Data Scientist/Data Analyst with 8+ years of experience working in analyzing large data sets, coming up with data driven insights for different companies and have worked in Statistical Modelling, Predictive Analytics, Data science, Machine Learning, Time series Analysis.

Established history of achieving goals through insightful listening, working as a problem solver, active team member and a recognized Team leader. Executed complex SQL queries to extract, analyze and manipulate data from large databases.

EDUCATION

Master of Science Grade:A 2019-2021

Elmhurst University

Majors: Data Science and Analytics

Master of Science GPA: 3.5/4.0 2002-2004

Kinnaird College University

Majors: Business Statistics

Thesis: Statistical anlysis and study of drug addicts in public hospitals.

Course Work: Mathematics, Statistics, Economics and Business Management.

Bachelor of Science GPA: 3.6/4.0 2000-2002

Kinnaird College University

Course Work: Mathematics, Statistics and Economics

AREAS OF EXPERTISE

Rich experience of going through all the steps of Data Analysis, the collection, transformation, and organization of data to draw conclusions make predictions for the future, and make informed data driven decisions

Used SQL queries to extract and analyzed data in my projects

Have used Tableau for visualization in my projects

Comprehensive knowledge of Machine Learning Process, having thorough understanding of various phases like Feature Engineering, training data, ML algorithm, model validation

Knows how to transform data into insight for making better decisions.

Extensive experience working with multi-geographies and vendors.

Ability to work in challenging environments and deliver high quality output to the stakeholders.

Comprehensive knowledge of Waterfall and Agile methodology.

Proficient in Python (Pandas, NumPy, Matplotlib,Scikit-Learn), SQL, Microsoft Office, Tableau, Rapid Miner, Salford Predictive Modular (SPM), SAS

Worked in multiple projects in Python, using Pandas for Data analysis, NumPy for scientific computation, Matplotlib for Plotting and Visualizations and Scikit-Learn library for Machine Learning tools

Worked in R programming language in a time series forecasting project

Experience in SAS in a project, used it for analysis

An effective leader with capabilities in motivating teams and maintaining deliverables as per the defined guidelines along with elevation of service standards for operational excellence.

CORPORATE EXPERIENCE

Infosys, United Airlines– From July2022- Till April 2023

Infosys, Hyundai Motors– From Jan 2022 - Jun 2022

Blue Cross Blue Shield- From Oct 2021- Dec 2021

Caterpillar – From Jun 2007-Jun 2011

Skills

Technical Skills

Management Tools

Word, Excel, PowerPoint, Draw.io

Technical Skills

Python, R, SQL, Julia, Power BI, Tableau, Rapid Miner, Minitab, Salford Predictive Modular(SPM) QDA Miner

Functional Expertise

Statistical analysis, Machine Learning, Predictive & Descriptive Analytics, Time Series modeling, NLP, Model development & Validation, Reporting & Dashboard creation, CRIPS-DM methodology

PROJECT DETAILS:

Independent Consultant May2023-July2024

Role: Data Scientist

Analyzed budget and expenditure data to assess the efficiency of resource allocation. Identify opportunities to streamline expenses, reduce costs, and maximize the impact of financial resources.

Conducted needs assessment by analyzing demographic data and community surveys. Identify areas of greatest need and prioritize program interventions accordingly

Analyzed financial data to assess the organization's revenue and expenses

Ran reports involving key insights derived from data analysis

To analyze data effectively and for statistical analysis used Excel, Tableau and SQL

United Airlines July2022-April2023

Role: Data Scientist

Developed an Analytics application to visualize the Flight schedules.

Built Decision models to make recommendations on Flight scheduling issues.

Developed Features to build models for Flight schedule optimization and lead POC to operationalize optimization

Integrated the metrics in UI. Built an application that can analyze, provide multiple dimension metrics, predicts schedule performance based on schedule’s characteristics and provide collaboration of resources (crew, fleets, aircraft, gates)

Worked with the client to understand the requirements

Coordinated with the offshore team

Ran SQL queries to get data from Redshift database

Hyundai Motors Jan2022-Jun2022

Role: Data Scientist/Analyst

Safety Office Data analytics system

Designed a system using machine learning and analytical tools that sends alerts for vehicle that could lead to safety concerns

Worked with multiple data sources, preprocessing in python

Used Pandas library for data analysis, NumPy for scientific computation and for plotting used Matplotlib library

Data from different data sources used for analysis and model development

Worked to implement statistical tools for anomaly detection and investigating potential defects

Remote agile methodology

Ran HIVE queries to get the data

Statistical Alerts and severity alerts were generated, statistical alerts were generated if the modified z-score based on Median and IQR values crosses the threshold

Used Tableau for the visualizations.

Defined and documented clear and complete detailed business requirements and functional specifications using the agile methodology from the Business team

Blue Cross Blue Shield Sep2021-Dec2021

Role: Data Analyst

Benefits Realization

Partnered with EPMO portfolio to evaluate inputs, outputs and the overall health of the processes and date, with the focus on telling the story

Recommendations were provided to improve the process, data and reporting improvements and single tool needed for the data storage for analysis

Data Analytics Consultant 2014-2019

Worked as a Data Analytics consultant for operational efficiencies and community outreach. Developed models to predict number of people attending various large events, helped in reducing cost and improve efficiency

Created model to predict when to open the center for community after covid lockdown

Generated reports and data sheets for various small business clients

Used python programming language to analyze and visualize data

Wrote and ran complex SQL queries

Caterpillar INC – (Caterpillar Logistics) 2007-2011

Role: Inventory Data Analyst

.

Worked for Inbound support Caterpillar Distribution center

Statistical and exploratory data analysis

Interaction with various business stakeholders for requirement gathering

Work with contract processors to reconcile part inventories in the systems and responsible for back-offs if required

Inventory reconciliation for Cat external client Land Rover North America. Adjustments, counts & investigation

Managing processes to ensure that Cat logistics client “Land Rover” inventory accuracy levels are maintained and improved.

Resolving stock record discrepancies by analyzing and interpreting various types of transactions to ensure correct record adjustments.

processing and managing dealer locator claims using SAP.

Running reports for faulty material.

Creating daily count sheets from the pending count list and sending the count sheets to the facilities.

Cycle count adjustments and working with India team.

Bin denials adjustments.

Inventory adjustment reports

Executed vital role as subject matter expert in 6 Sigma projects. Played key role in “LRNA Transition of RAM Reconciliation” project. The project involved replication of existing processes and transition from Morton Record Accuracy Management (RAM) to Bangalore. Specifically, transition of daily processing of low dollar reconciliations of four LRNA warehouses and corresponding inventory adjustment reporting to Bangalore staff.

RECOGNITION:

Received recognition for undertaking key responsibilities and effectively executing the transition of inventory adjustments to the India team, meeting cycle counts deadline and following up to sustained process control, leading to phenomenal progress in regular inventory adjustments.

COURSE PROJECTS:

Credit Risk analysis:

Robust data with 74 attributes, after cleaning dataset and feature engineering created a model in Python to predict credit defaulters of financial institution using Pandas, Numpy, Matplotlib and Scikit-Learn libraries in Python.

Pandas helped in the data analysis, used Numpy for Scientific computations, Matplotlib for plotting and visualization and Scikit-Learn for the machine learning tools.

completion of the model provided notable insights of important features helpful in prediction of active loan default.

The model and findings pointed to recommendations involving when it may be appropriate to write off a high-risk loan and loans should be evaluated in the future.

Predicting patients with cardiovascular disease:

Developed a model that predicted if a patient has cardiovascular disease.

After exploratory analysis of the dataset in Python, did feature engineering, created models, and finalized the model for deployment.

Pandas helped in the data analysis, used Numpy for Scientific computations, Matplotlib for plotting and visualization and Scikit-Learn for the machine learning tools.

Used Logistic regression model to do the prediction

Time Series forecasting:

Created a model in R to forecast IL Air travel.

Studied the air travel of people travelling from IL and to IL, observed lack of trend but found seasonality.

Selected ARIMA model for prediction as it had the smallest residual standard deviation, and it helps in forecast the air travel.

Contact this candidate