Data scientist Kiran Vanukuri , Engineering & Science

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.

I am a Data Scientist with 2+ years of experience in various domains such as Machine Learning , Natural Language Processing, Speech Recognition, Visualisation. Detailed information about my work: -Worked on Exploratory Data Analysis to extract meaningful insights from data using summary statistics and visualisations. -Built models in order to predict the sentiments of a use case. -Experienced in Natural Language Processing concepts such Word Embeddings, Named Entity Recognition, Sentimental Analysis, Dependency Parsing. -Believe in building an end-to-end application for business needs. -Additionally have a basic idea of Cloud Computing. Highlight projects: -News Title & Headline Sentimental Analysis. Predicted the sentiments of the title and headline of the news article -Restaurant Aggregator and Food Delivery Application EDA Carried out extensive exploratory data analysis on the dataset and did visualisation for better understanding. -Crop Advisory for Farmers Built a portal for farmers, predicted and suggested crops to them. I have also received scholarships for Intel Edge AI and DataCamp: DataScience by Facebook Developers Circle.

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.

 Identify and develop projects to optimize manufacturing processes, including the use of engineering methods (Six Sigma) for the continuous improvement of processes and products. Lead the implementation ensuring that the business objectives and expected quality standards are met.  Submit changes (creation and changes of structures, procedures and documents) through the company's change control systems. Validate and implement changes in products, processes and equipment.  Prepare and execute the protocols and reports of qualification for equipment, computer systems and utilities.  Ensure that project deliverables comply with internal procedures and customer requirements.  Provide validation support during installation, commissioning and production for new and existing equipment and systems.  Create procedures (SOP) for handling production equipment and instruments for calibration.