Sr. Data scientist Resume

SUMMARY:

Strong aptitude and practical experience with machine learning techniques and algorithms (Classification, Clustering, Association rules, Ensemble model and Deep learning)
Three years of experiences in Python and data analysis using python (Pandas, Numpy, Matplotlib, Scipy, Scikit - learn, Tensorflow)
Seven years of Experience in SAS programing ( SAS/EG, SAS/MA, SAS/EM, SAS/CI,SAS /MACROS, SAS/SQL)
Good knowledge of PySpark and Scala (spark streaming, MLLib, spark SQL, Graphx)
Extensive experience in managing data in SAS files, merging SAS data sets and data manipulations in SAS
Proficient in using Python,SAS, Scala, SQLand Hive for the extraction, validation, testing and modeling of data
One year of experiences in Hive (data manipulating)
Long experience in querying from various databases (Oracle, MS SQL, Linux, Teradata and Hadoop)
Strong technical abilities including skills in statistical analysis, predictive modeling
Good knowledge of AWS solutions and cloud computing
Excellent understanding of development processes and agile methodologies

PROFESSIONAL EXPERIENCE:

Sr. Data scientist

Confidential

Responsibilities:

Created machine Learning Model on click stream data using Spark in zeppelin environment
Built customer segmentation to fulfill client’s goals and objectives for digital marketing.
Created multichannel campaigns in SAS CI studio and deliver them in Adobe audience manager.
Designed and ran A/B test for measure the effectiveness of the campaigns.
Analyzed and processed complex data sets using advanced querying and analytics tools.

Data scientist

Confidential

Responsibilities:

Built machine learning models (Linear and Logistic regression, Gradient Boosting, Random Forest, SVM, Neural network, etc.) from development, validation, through to deployment in production.
Ensured data quality and dealing with Imbalanced data to feed the models properly.
Created and presented models for potential customer segmentation to target in marketing. On Average achieved 3 times better returns vs historical random model’s performance previously used.
Analyzed and processed complex data sets using advanced querying, visualization and analytics tools.
Identified, measured and recommended improvement strategies for models from other vendors.

Senior developer

Confidential

Responsibilities:

Developed Python codes to track working hours, absences and payments of employees and build different reports for payroll team using Python’s libraries.
Modified existing Python scripts and created new codes to improve ease and speed of modification as well as consistency of results.
Creating macros to develop SAS programs for credit risk modeling and calculating risk metrics such as Delinquencies, PCL, ECL, WRITE OFF, RECOVERY, PD, LGD and EAD.
Developing and implementing innovative SAS strategies and programs for creating database tables in projects with large, diverse, data source files.
Restructuring incoming data using SAS code by reformatting, importing, sorting and merging data, in order to easily be used for Ad-hoc queries by report team.
Scheduling SAS jobs in UNIX for updating the data tables in production regularly.

Confidential

Responsibilities:

Conducted machine learning methods for selecting features, building and optimizing classifiers and predicting models.
Generated monthly and weekly reports, using SAS, SQL, R and Pythonoutputs for board of directors for monitoring purposes on customer and services.
Obtained a score for scorecard model and determined the probabilities of default and validated the credit scored model for the client of Refah Bank (which was belong to the organization).
Empowered business users to make data driven decisions by providing them with models, reports, charts, tables and graphics generated using SAS,SQL, R and Python.
Applied advanced statistical models to perform patterns identification, and add predictive analysis to enhance its insights.