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Senior Analyst/data Scientist Resume

Houston, TexaS

SUMMARY:

  • A Bi - lingua (R and Python) Machine Learning practitioner with strong proficiency in methods
  • ARIMA, ARIMAX, GARCH, Facebook Prophet, LSTM.
  • Support Vector Machines, Random Forest, Decision Trees, Logistics Regression, XGBoost
  • Simple Linear, Multiple Linear, Polynomial, Support Vector Regression, Random Forest Regression, and Least Square Method, Ridge Regression, Elastic Net Regression, Lasso Regression, XGBoost
  • NLP, Deep Learning, Ensemble Learning, Hidden Markov Model, LDA, PCA
  • Scikit Learn, TensorFlow, Keras, Tidyverse, dplyr and other libraries from both R and Python.
  • Gradient Descent, RMSE, Maximum Likelihood Estimation, Binary Cross Entropy Loss, Combinatorial Optimization etc.
  • Storytelling with data and pattern recognition, recreating business scenarios in situations where data is limited.
  • Looking to join an organization that understands and appreciates the value of Machine Learning and Artificial Intelligence in this fast-changing technological world we live in, where I can use my vast knowledge of Machine Learning Algorithms and Statistical Analysis to help business leaders make smart business decisions that would drive Sales and reduce G&A.

SKILLS:

Operating systems: Linux, windows

MS Office: Word, Excel, PowerPoint, Access and outlook.

Programming Languages: Python, R, SAS, SQL Server, MatLab, Git, Markdown, LaTex

Databases: Microsoft SQL, MS Access

Statistical Tools: R, Python, SAS, MatLab, JMP, AVAYA, MS excel, Tableau 10.5, Azure

PROFESSIONAL EXPERIENCE:

Confidential, Houston, Texas

Senior Analyst/Data Scientist

Responsibilities:

  • Moved the CX Predictive Analytics team from using simple forecast methods like Moving Average for customer contacts predictions to using ARIMA Time series and recently moved further to now using an ensemble model of CNN, Facebook Prophet and ARIMAX which has achieved an accuracy of >95% week over week.
  • Used Natural Language Processing and core Machine Learning to derive call drivers and enrich customer experience
  • Build ML and deep learning Models like Churn, regression, classification models as needed for different forecasting/predictions as required by different project managers in CX.
  • Analyze NPS data, investigate what the key drivers to NPS scores are and make recommendation to VP, CX on how to improve them.
  • Optimize models using different methods such as parameter tuning, gradient descent, combinatorial optimization etc
  • Report on accuracy of models to VP, Customer Experience
  • Built and maintain an eighteen-month rolling forecast for customer contact for all JE regions for Workforce to use for capacity planning
  • Performed univariate and multivariate analysis on the data to identify any underlying pattern in the data and associations between the variable.
  • Built a regression model to predict customer renewals based on different independent variables as seen.
  • Created and maintain CS department budget

Confidential, Houston, Texas

Statistical Analyst

Responsibilities:

  • Established dependency between customer profile and renewal rate, and used this to create a churn model, that achieved >88% accuracy Month over Month in customer renewals using XGBoost.
  • Helped develop a model that calculated how much customers would be disconnected each month for nonpayment using ARIMAX
  • Created a model that grouped customers into three credit band; High, Mid, Low then proved the correlation of credit group to customer tenure and value; value in terms of whether they would leave with an unpaid balance or not.
  • Created Regression models for different ad-hoc projects as requested by Ops department.

Confidential, Huntsville, Texas

Graduate Assistant

Responsibilities:

  • Graded for professors as assigned.
  • Worked as a supplemental instructor in select freshman and sophomore classes teaching Calculus II.
  • Tutored students at the Academic Success Center (ASC).
  • Collaborated with professors on Research works with focus on application of mathematics to biological systems using mathematical modeling.

Confidential

Data Analyst

Responsibilities:

  • Managed Excel spreadsheets and maintain data currency to ensure accurate data availability for managers and decision-makers.
  • Developed and implemented standard operating procedures to bridge data gaps and resolve related issues.
  • Automated the consolidation, reconciliation, and calculation of reports, used for funding, cash movements, journal entries, bookings, and statements between Clearing House, Clients, Custodian Banks, and Internal Systems.
  • Predicted trend analyses using complex Excel Macro, power pivots, Power View to analyze efficiency performance and to predict future level of operational activities.
  • Used Excel VBA/Macros queries to make reports in different styles and then distributed them as PowerPoint slides to management team

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