SUMMARY

• Results - oriented, visionary Data Scientist with ~5 years' experience in machine learning and deep learning and Masters' degrees in Data Analytics and Political Economy with focus on Statistics, Econometrics, Machine Learning, and Political events’ predictions. Worked with teams in integrating data science and analytics into decision making and portfolio of products and services. Led teams in implementing cutting-edge solutions, provide thought leadership and prototyping enterprise data science solutions.
• Led team of sizes 3 people (onsite and offshore) providing leadership, modelling and mentorship to more than 10 projects.
• Strong leadership, team management and problem-solving skills
• Worked closely with business, data governance, SMEs and vendors to define data requirements.
• Evaluated 3rd party data vendors and acquired data to increase model accuracy.
• Built models such as LSTM, keras on Tensor Flow, HMM, Random Forests, k-NN, logistic regressions, time series models using packages such as ggplot, dplyr, numpy, sci-kit learn, pandas, matplotlib, etc.
• Experience building NLP models using word embedding, Bag of n-grams, genism, word2vec.
• Automated by building workflows to extract data from various REST APIs and databases, processing responses, data transformations in python and R.
• Established feedback loops, automated processes, platform integrations, optimization models, models to increase user experience.
• Implemented cutting-edge solutions using on-premise and AWS solutions such as S3, Spark, MySQL, Hadoop, EMR, Aurora, Glacier, MongoDB, Cassandra, Elastic Search, Logstash, Kibanna, APIs, EC2, Lambda, Quick Sight.
• Implemented and proposed use-cases ranging from statistical analysis and testing, churn prediction, Time Series forecasting, anomaly detection, Customer LTV, text mining, A/B testing for feature selection, dashboards.
• Reported analytical findings to C-level executives using dashboards built in Tableau, Qlik View, R-Shiny.
• Managed teams to perform data analysis on classification and forecast models, statistical models, risk analysis and solved data-driven problems using SPSS, SAS E-Miner, R, SAS, Python, E-Views, Tableau, Qlik.
• Published Tableau reports to clients on a weekly basis and presented a monthly graphical summary to clients.

CORE COMPETENCE

• SQL
• MS SQL Server
• MySQL
• MICROSOFT SQL SERVER
• Hadoop
• Linux
• Javascript
• Python
• R
• Hadoop
• Tableau
• Business Intelligence
• Unix Administration
• Adobe
• Coding
• Apache
• C++
• CMS
• Database Development
• Database Administration
• Data Entry
• Data Analysis
• Data Mining
• Big Data
• Mongo DB
• AWS
• Deep Learning
• Machine Learning
• Project Management
• Data Management
• Data Warehousing
• BI
• Excel
• Essbase
• Fisma
• Hyperion

TECHNICAL SKILLS

PROGRAMMING LANGUAGES: Python, R, SAS, C, Matlab, Java, SQL, Hive, Linux, VBA Macro, Linux, HTML, CSS, JavaScript, and Bootstrap.

TOOLS & DATABASES: RStudio, python, Spark, AWS, SPSS, SAS, Hadoop, Hive, MongoDB, Cassandra, Zeppelin, S3, Aurora, Glacier, Elastic Search, EC2, Lambda, Quick Sight, Tableau, Qlik, Adobe Site Catalyst, Google Analytics, MS Visual Studio, Excel, MS PowerPoint.

PROFESSIONAL EXPERIENCE

Data Scientist

Confidential, Buffalo, NY

Responsibilities:

• Explore data using Python or R before preparing data for model training by writing simple algorithms for correlation, summary statistics and plotting for easy visualization.
• Use K-means algorithm to determine cluster centroids before assigning data to training clustering model and then applying SQL transformation to retrieve results.
• Evaluate predictive models using Azure Machine learning ad-ins in Excel by extracting experimental API from training studio thereby saving time and cost.
• Perform stream processing using Hive and batch processing using Spark for preparation of test data for social media analysis. text mining with MapReduce in Hadoop, and presented the results using Link Graphs in SAS E-Miner Used Power BI, Excel Pivot and Tableau to visualize results for non-technical colleagues.
• Perform explanatory data analysis, Feature Engineering with python and data pre-processing functions like ETL, imputation of missing data, capping skewed values, binning, duplicates using Python Pandas library.

Data Scientist

Confidential, Buffalo, NY

Responsibilities:

• Analyzed time series data related to credit card payments of customers in the USA using descriptive statistics and cluster analysis.
• Work with internal and external datasets, provide analyses in development of statistical models for analyzing asset performance, securities data, risk exposure and derivative pricing.
• Used ggplot2, dplyr, lm, e1071, rpart, random Forest, nnet, tree packaged in R to understand complex interrelationships and effects among platform.
• Then provide highly analytic consulting before implementing technical expertise to assist business unit in meeting project objectives.
• Used Pandas, NumPy, Seaborn, SciPy, Matplotlib, Scikit-learn in Python for developing machine learning models using ML algorithms such as linear regression, Decision trees, SVM and Random Forests then conducting sensitivity tests to compare project models.
• Built interactive and intuitive dashboards using Tableau, Power BI to communicate key results and metrics to the Risk Management team.

Jr. Data Scientist

Confidential, Buffalo, NY

Responsibilities:

• Database maintenance with SQL and related queries from DB2 and Oracle DB, OBIEE, Excel, Access DB. Performed data extracting and storage, then run tests to maintain efficient cloud performance.
• Performed cleansing, anomaly detection, and Pre-processing of structured and unstructured data with ETL technique utilizing in Hadoop to prepare data for training.
• Built predictive models to predict churn of customers & 'Next product to buy' products using regression and classification machine learning models utilizing processed data from Hadoop, then using Python to rewrite existing and new algorithms for evaluation and visualization.
• Participated with other operations and IT staffs in systems development through technical analysis with R, Hadoop, Python and SAS then conducting user acceptance testing.
• Work experience with Project management & Collaboration tools: MS Project, MS PowerPoint, MS Excel, Atlassian Confluence, JIRA.

Data Analyst

Confidential, Amherst, NY

Responsibilities:

• Part of the campaign team, where I analyzed voting data, patterns and recommended awareness strategy.
• Created Tableau scorecards, dashboards using Stack bars, bar graphs, scattered plots, geographical maps, Gantt charts using show me functionality.
• Worked as Data Architects and IT Architects to understand the movement of data and its storage and ERStudio9.7
• Processed huge datasets (over billion data points, over 1 TB of datasets) for data association pairing and provided insights into meaningful data association and trends
• Participated in all phases of data mining, data collection, data cleaning, developing models, validation, visualization and performed Gap Analysis.