Data Analyst/ Data Scientist Venkatesu Chowdam Venkatesu Chowdam Venkatesu Chowdam Venkatesu Chowdam, Engineering & Science

Summary ● Stress/Structural Engineer in the aerospace industry with a demonstrated history of working as a design engineer. Skilled in Stress Analysis, Computer-design Design, Communication, Manufacturing, FEMAP, and Product Development. Experience ● Stress/Structural Engineer | January 2018 – present o Responsibilities: ▪ FE modelling and analysis of interior monuments for A350 XWB, preparation of certification reports (IFL, QSR, etc.) in order to show regulatory agencies requirements compliance. ▪ Conducts stress analysis on aircraft interiors (galleys) on A350 XWB and related components to evaluate ability to withstand stresses imposed during flight. ▪ Analysis the ability of structural components individually to withstand stress imposed by static and dynamic loads due to operational conditions. ▪ Studies specification and design requirements to determine strength and bending characteristics of parts and assemblies. ▪ Give inputs to the design based on analysis of the current design and suggest necessary modifications. ● Design Engineer | January 2017 – July 2018 o Production Workflow Checker ▪ Responsible for assessing and ensuring all designed products are in accordance with customer requirements and should be possible to manufacture in the production line. o Change management peer-reviewer/originator ▪ Supported Change Management Team for peer-reviewing/creating changes in the design and ensuring that it meets customer requirements. o Weight Saving Team ▪ Supported in reducing metallic sheet reinforcement’s (doubler) thickness in strategic locations to save overall weight of the interior monument without sacrificing structural integrity. Skills ● Practical FEMAP user (linear analysis with limited knowledge to non-linear analysis) ● Design Engineering / Design Change ● Translate concept designs into Computer Aided Design (CAD) models. ● Practiced CATIA user ● Root-cause analysis ● Knowledgeable in product configuration ● Knowledgeable in Product Life Cycle Management ● Easy to adopt with any working environment

A highly competent data scientist with experience of developing a wide range of innovative machine learning and neural network models for problems like Deep Fakes, Language Modeling, Credit Card Fraud Detection, and Early Diagnosis of Autism. Ability to use data, statistics, and machine learning for finding complex data patterns that drive meaningful impact on the business. I am looking for the opportunity to build a challenging career and apply my skills in an innovative and simplified process. I enjoy working in a team and deliver data-driven results.

I have worked with Accenture as ASE - Associate Software Engineer. Have good knowledge of Machine Learning and Deep Learning. Python's Library for Data Analysis - Pandas, NumPy, Matplotlib, Seaborn. Statistics along with Microsoft Power BI for Business Intelligence Tool, Microsoft Excel, MySQL, Oracle. Well versed in SDLC and Agile Methodologies. Aware with few IDEs - Jupyter Notebook, Eclipse, PyCharm, Atom Experienced with HTML5, CSS3, JavaScript, Core Java, Servlet, JDBC, Python, MYSQL, Oracle, SQLite, which helps to develop a full project.

A certified Applied Data Scientist with experiences focusing on statistics analytics and machine learning. Familiar with statistics modeling, feature engineering and commonly used machine learning algorisms. My last project was working on an anomaly detection project for Microsoft Digital Stores using Microsoft cognitive service with some python public packages and Microsoft internal Bias Test library. • Experienced descriptive statistics and advanced analytics in Cosmos big data environment for MSCOM Digital Store. • Experienced causal impact modeling for camping incrementality analysis. • Experienced reinforcement learning modeling using Markov Decision Process for MSCOM online customer behavior analysis and action recommendations. • Experienced MS stores KPIs anomaly detection and root cause analysis conduct with forecasting model to reduce the false alerts. Writing python class library for internal use case. • Experienced Azure VM auto scaling schedule time series forecasting, classifications for MS Azure Subscription Automation Team. • Participated in data science professional activities, o Cortana Intelligence Competition Project 2016 – Decoding Brain Signals Achieved top 10th in public leader boarder - accuracy 81.875% in public test dataset. Achieved top 12th in private leader boarder - accuracy 80% in private test dataset. Program Language: R Platform: R Studio, MS Azure Machine Learning Web service. Algorism: LASSO most like hood features selection and logistic regression o Kaggle Competition project - Classify Handwritten Digits Using MNIST data Program Language: R “mxnet” deep learning model, accuracy: 99.429% Program Language: Python “Tensorflow” deep learning model, accuracy: 99% • Experienced simulation science tool development using modem web technologies and PowerSim SDK.