SUMMARY

• Data scientist with 7 years of experience in transforming business requirements into analytical models, designing algorithms, and strategic solutions that scale across massive volumes of data.
• Experience and domain knowledge in various industries such as media and technology.
• Involved in the entire data science project life cycle, including Data Acquisition, Cleaning, Data Manipulation, Data Mining, Machine Learning Algorithms, and Data Visualization.
• Experienced with machine learning algorithms such as linear regression, logistic regression, decision tree(CART), random forest, Adaboost, gbdt, SVM, k - nearest-neighbors, naïve Bayes, Bayesian network, k-means clustering, Gaussian mixture model, Kalman filter, neural networks, recommendation system design and more.
• Strong skills in Statistics methodologies such as hypothesis testing, ANOVA, Monte Carlo simulation, principle component analysis and correspondence analysis, ARIMA time series analysis, structural equation model.
• Worked with model validation and optimization using cross validation, and regularization.
• Proficient in Python 3.x with NumPy, Pandas, SciPy, Scikit-learn, matplotlib, plotly packages.
• Extensively worked on R 3, SAS 9.4, SAS Enterprise Miner 14.1 and Enterprise Guide 6.1.
• Strong skills in web analytics tools like Google Analytics and Google Adwords.
• Solid ability to write and optimize diverse SQL queries, working knowledge of RDBMS.
• Adapt knowledge of big data tools like Hadoop 2.0 (HDFS, Hive, MapReduce), Spark 2.0.1 (PySpark, SparkSQL, Spark ML).
• Deep understanding of building, publishing customized interactive reports and dashboards with customized parameters and user-filters using Tableau 9.4/9.2.
• Excellent understanding of SDLC (systems development life cycle), Agile and Scrum.
• Extensive experience with version control tool Git.
• Effective team player with strong communication and interpersonal skills, possess a strong ability to adapt and learn new technologies and new business lines rapidly.

TECHNICAL SKILLS

Languages \Big Data Tools: \: Python 3.3/2.7, R 3, SAS 9.4, VBA, SQL, \Hadoop 2 (Hive, HDFS), Spark 2.1 \HiveQL\(PySpark, SparkSql, Spark ML), AWS\

BI Tools \Operating Systems: \: Tableau 9.4/9.2, SharePoint 2016/2013, \Windows 10/8/7, UNIX, Linux\MS Office (Word/Excel/PowerPoint/Visio)\

Packages \Database: \: Python (Numpy, Pandas, Scikit-learn, Scipy and \Oracle 11g, Access 2013, SQL Server 2014/\Matplotlib, pykalman, pydlm), R (caret, dplyr, \2012, MySQL 5.5, HBase 1.2, MongoDB 3.2\Glmnet, lavaan, bnlearn, ggplot2, GoogleVis, \Shiny)\

PROFESSIONAL EXPERIENCE

Confidential, Philadelphia, PA

Data Scientist

Responsibilities:

• Extracted, cleaned and manipulated machine log data from MySQL, AWS S3 and Splunk.
• Generated dashboards to monitor Xifinity’s entertainment operating system X1’s performances, and to make sure the products are reliably available, using Tableau.
• Developed matrix to measure customer experiences and detected buggy devices for the engineers to investigate before it reaches a certain point that customers have to call for help.
• Performed clustering analyses to segment customers into different groups based on their service experiences and product engagement using Python and PySpark.
• Performed classification models to search for the most impactful features to our KPIs.
• Collaborated with the product team to test newly developed product features.
• Visualized analysis results using python Plotly and Tableau dashboards and presented findings to executive management on a weekly basis.

Environment: Python 3.x, MySQL5.5, Spark 2.1, Splunk, AWS S3, Databricks

Confidential, Irvine, CA

Data Scientist

Responsibilities:

• Coordinated with field operations and management team, in order to understand the origins, contents, and structure of datasets, ensured that objectives were able to be met
• Performed SQL queries to extract field report data from MySQL database
• Extracted and organized information from manually conducted cases and exported to structured data using Python with re (regular expression)
• Performed initial descriptive data analysis and generate statistical reports
• Developed classification algorithms to identify wire down incidents as to whether they are energized or non-energized and automated the detection procedure
• Established an executive dashboard to demonstrate the project achievement and effectively communicated the results and reported to senior management

Environment: MySQL5.5, Python 2.7, Microsoft Office 2013 (PowerPoint/Word/Excel), Tableau9.4

Confidential, New York, NY

Data Scientist

Responsibilities:

• Communicated and coordinated with other departments to collected client business requirements
• Conducted data exploratory analysis on survey data to learn customer feedback and response
• Utilized survey data to evaluate brand health, understand customer path-to-purchase life cycle and sharpen the product positioning with statistical methodologies such as hypothesis testing for both single and multiple answer questions using Python
• Identified competing brands based on survey data with correspondence analysis using Python
• Compared POEM (paid, owned, earned media) performance concerning various measurement of awareness with Bayesian network and SEM (Structural Equation Model) using R
• Estimated the impact of TV advertisement in order to evaluate ROI with Kalman filter using Python
• Built and optimized TV program rating prediction models with machine learning algorithm such as lasso regression and random forest using Python
• Cooperated with tech department and set up an automated system to select most effective marketing channels
• Validated and selected models using k-fold cross validation methods, error metrics and worked on optimizing models for higher accuracy
• Created data visualization using Tableau, R ggplot2, Python matplotlib, MS Visio and PowerPoint
• Reported weekly progresses and presented final results to partners

Environment: Python 2.7 (Numpy, Pandas, Scikit-learn, pykalman, pydlm), R 3 (caret, glmnet, Lavaan, bnlearn, ggplot2), MS Excel 2013, Tableau 9.4, MS PowerPoint 2013, MS Visio 2013

Confidential, Hartford, CT

Data scientist

Responsibilities:

• Performed SQL queries to extract parking lots transaction data from Oracle SQL database
• Examined transaction data, identified outliers, inconsistencies and manipulated data to insure data quality and integration using Numpy and Pandas in Python
• Worked on problem analysis, solution proposal based on exploratory analysis of parking lots performance.
• Conducted research and created a report that emphasizes knowledge of brand heritage, business facilities and parking services to add context in support of data analysis
• Used clustering technics to define customer segmentations and targeting each with specific strategies
• Built time series models (ARIMA) to forecast the occupancy of parking lots
• Performed cost-benefit analysis to quantify and validate the business suggestions
• Scrapped customer reviews from Yelp, Facebook, Twitter and other third-party sources, stored in MongoDB and conducted text mining and sentiment analysis for both Confidential and its competitors’ performance at Oakland airport and conducted analysis like logistic regression to identify the most important features that have influence on customer experience
• Implemented web analytics for the airport parking website to enhance the awareness over its competitors
• Created visualization dashboards and apps using Tableau and R Shiny for business inferences

Environment: MySQL 5.5, MongoDB 3.2, Python 2.7(Numpy, Pandas, textmining, nltk, Scikit-learn, pySpark), Tableau 9.4, R 3 (Shiny)

Confidential

Statistical modeler

Responsibilities:

• Performed requirement analysis by gathering both functional and non-functional requirements based on interactions with the process owner and stake holders.
• Interacted with department heads to finalize business requirements functional requirements
• Gathering data information from multiple sources using analytical techniques, and presenting data that visually communicates to users important aspects of the data to optimize the flow of information
• Pulled data from different databases and migrated data back and forth using SQL
• Conducted data analysis including application of cross-functional use-cases that utilize advanced techniques such as linear/logistic regression, decision trees with SAS leveraging huge datasets and provided the results of the analysis to offsite teams to support key business functions.
• Worked towards establishing best-practice to evaluate and improve the data quality for analytical use
• Built advanced analytics models to identify significant features from the finalized datasets
• Liaised with the other client-facing teams to help the client understand nuances of the model details
• Utilized Data Mining and Statistical Analysis skills for proposing strategy to acquire future projects

Environment: MySQL 5.5, SAS 9.4, R 3, MS Excel 2013, MS PowerPoint 2013, MS Visio 2013

Confidential

Business Analyst

Responsibilities:

• Analyzed B2B/B2C platforms to collect potential customer data and stored them in MySQL database
• Filtered raw data from providers to position potential customers and improved the filtering process by using search engine and greatly raised work efficiency
• Coordinated activities between the business house and technical staff, in developing new methods, policies, and procedures to meet the business needs
• Dived on key business, product, financial, merchant and consumer metrics to develop insights and strategy
• Created data for the most likely events (e.g. bill surcharge, late fee etc.) that could affect predictions
• Successfully helped managers recommend accurate strategic plans and implement marketing and business decisions. Utilized skills in software applications such as SAS Enterprise Miner/Guide to help managers validate strategy using decision tree analysis and created surplus and analyzing sales data for industry

Environment: MySQL 5.5, Salesforce, SAS Enterprise Miner 14.1, SAS Enterprise Guide 6.1, MS Office 2013 (PowerPoint/Word/Excel), SPSS 19, R 3

Confidential

Business Analyst

Responsibilities:

• Collected and analyzed sell-in and sell-out data, gathered market and internal information to define strategies
• Cross-referenced data from the sales force, both internal and external market studies and marketing in order to have a comprehensive overall understanding of the business
• Managed complexity in terms of shopper, consumers and turnover data, performed analysis like simulation, optimization, conjoint and Monte Carlo Markov Chain using Excel, SPSS and R
• Reported on the analysis of market trends, business performance and various levers such as pricing, mix management, formats and promotions
• Shape and disseminate analyses and syntheses to help decision makers to drive business activity, translate recommendations for internal plans and business plans
• Support the domain “business owners” in the definition of their needs and translate them into recommendations for development and improvement of model applications.

Environment: SPSS 19, MS Office 2013 (Excel/PowerPoint/Visio/Word), R 3