Senior Data Scientist

Senior Data Scientist

Requirements

• Master’s degree or the equivalent in Statistics, Analytics, Computer Science, Engineering, or related field plus 2 years of data science experience or related experience; OR Bachelor’s degree or the equivalent in Statistics, Analytics, Computer Science, Engineering, or related field plus 5 years of data science experience or related experience.
• Must have experience with: Object-oriented, procedure-oriented and database programming languages including Python, Java, R, Linux Commands, and MYSQL; Developing both supervised and unsupervised machine learning prediction models including XGBoost, Random Forest, deep neural networks, K-means clustering, and graphical network models; Exploratory Data Analysis with Statistical theories and implementation, including statistical analysis, hypothesis testing, and statistical inferences; Data processing include text content processing, web scrapping, data mining, and data frame processing with user defined functions in programming; Creating features and developing feature engineering to add new indicators to improve prediction model with Python; Coding and reviewing on multiple coding platforms including Google Cloud Platform, Microsoft Azure related Platform, and GitHub; Model assessment and validation with model fit testing, tuning, and validation techniques including Chi square, ROC curve and root mean square error; Data Visualization with Tableau, Tableau Prep, Power BI, Gephi; Conducting complex data transformation, calculation and cleaning in Tableau Prep in preparation for data visualization; Application of NetworkX python package for network structure analysis in big data; Application of PySpark and sklearn in Python for model development, data manipulation and analysis; Application of Matplotlib, NetworkX, Graphviz, Plotly, GGplot in python, and R libraries for customized data visualization; and Coding with geospatial packages including GeoPandas, Shapely, Pyproj, Geoplot, and Rasterio for spatial data processing, cleaning and analysis.

Responsibilities

• Develop custom data models to drive innovative business solutions.
• Build complex data sets from multiple data sources, both internally and externally.
• Conduct advanced statistical analysis to determine trends and significant data relationships.
• Build learning systems to analyze and filter continuous data flows and offline data analysis.
• Train algorithms to apply models to new data sets.
• Validate models and algorithmic techniques.
• Scale new algorithms to large data sets.
• Combine data features to determine search models.
• Research new techniques and best practices within the industry.
• Utilize system tools including (MySQL, Hadoop, Weka, R, MATLAB, ILog).
• Responsible for analyzing large data sets to develop custom models and algorithms to drive business solutions.
• Work on project teams in order to provide analytical support to projects (for example, email targeting, business optimization, consumer recommendations) for Walmart eCommerce.
• Responsible for building large data sets from multiple sources in order to build algorithms for predicting future data characteristics.
• Those algorithms will be tested, validated, and applied to large data sets.
• Responsible for training the algorithms so they can be applied to future data sets and provide the appropriate search results.
• Responsible for researching new trends in the industry and utilizing up-to-date technology (for example, HBase, MapReduce, LAPack, Gurobi) and analytical skills to support their assigned project.
• Work with cross-functional partners across the business.
• Develop models of current state in order to determine needed improvements.
• Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales.
• Provides and supports the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities.

Preferred Qualifications

No preferred qualifications provided.