Data Scientist Resume

SUMMARY

12+ years of Predictive analysis, Data science and Machine Learning experience.
Dedicated to achieving growth through new initiatives and improving the design and execution of innovative techniques to find deeper insights and discoveries within the data.
Extensively used structured and unstructured big data querying from SQL databases using programming languages like Python and R.
Created and presented models for different projects which impacted management decisions.
Managed more than 40 projects and improved business process in more than three companies
Coordinated a team of 10 data scientists working on 6 different projects.
Cloud computing experience: Microsoft Azure, AWS, and IBM cloud.
Adaptability and propensity to learn new coding languages and programs.

TECHNICAL SKILLS

Advanced: Python, Perl, Fortran, Mathematica, and Matlab

Intermediate: SQL, Spark, Hadoop, MapReduce, and Tableau

Basic: R, Hive, Pig, Impala, and Scala

Machine Learning: Supervised and Unsupervised machine learning, Deep learning, and Natural Language Processing

Python Tools: Pandas, Recommender Systems, Regression, Scikit - learn, SCIPy, Jupyter Notebook, Folium, Matplotlib, NumPy, Seaborn, Db2, Databases, SQL, Open Source Tools for Data Science (Jupter, RStudio, Watson Studio, Zeppelin)

Cloud computing: AWS, Cloudera, Databricks, Microsoft Azure, and IBM Bluemix

PROFESSIONAL EXPERIENCE

Confidential

Data Scientist

Responsibilities:

Lead Quality Assurance data Management in different instruments, evaluation and analysis of QA/QC data, identifying trends and shift and taking corrective actions.
Project on maintenance cost reduction using predictions. Reduced maintenance cost by 40%.
Project on Cancer stage prediction and treatment. developed Predictive models using a variety of techniques, including Artificial Neural Networks (ANNs), Bayesian Networks (BNs), Support Vector Machines (SVMs) and Decision Trees (DTs) in cancer stage prediction and treatment.
Managed a high-volume data (workload) within a deadline-driven environment consistently exceeding performance benchmarks in all areas (speed, accuracy, volume).
Demonstrated high energy/creativity, a passion for analyzing complex big data sets, strong communication and project management skills

Confidential

Data Scientist /ML developer

Responsibilities:

Worked on a team using statistical, mathematical, and predictive data models to bring insights and answers to complex business questions and investigations
Applied machine learning algorithms, logistic regression, random forest, SVM, Neural Networks, k-means, to address consumer retention, churn and recommendation systems using Python (scikit-learn) on Microsoft Azure.
Project successful in retaining 10% of customers in churn group.
Analyzed and visualized geospatial data sets using Python (Panda, Seaborn, matplotlib) and Tableau.
Performed fraud detection analysis using deep learning (Python TensorFlow) and random forest classifications (Python scikit-learn).

Confidential

Data Scientist

Responsibilities:

Applied Natural language processing to classify Foursquare online review based on the text content in the review using Python (NLKT).
Analyzed content-based and collaborative-filtering movie recommender system using Apache Spark with Scala on Databricks and AWS.
Project on Time Series forecasting with ARIMA.
Cloud computing experience using Apache Spark and MapReduce on AWS, Databricks and IBM Analytics

Confidential

Data Scientist

Responsibilities:

Worked as Instructor of advanced statistics and as clinical research advisor: have led a team of colleagues and students in research data analysis and predictive modeling like regression.
Authored and published more than 12 research articles on peer reviewed international journals. In these publications I was responsible on overseeing proposal development, verifying data collection methods, cleaning the data, do inferential and predictive analysis using Python. These publications have been cited more than 120 times by other authors.
Organized and led virtual teams and moderated distance learning (ML-web, blackboard). Team members were from 7 different countries in the world.
Highly efficient project management skills

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