Data Scientist

  •  

Tampa, FL

Not Specified years

Posted 167 days ago

  by    Kumara Swamy

Responsibilities:

* Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.

* Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.

* Assess the effectiveness and accuracy of new data sources and data gathering techniques.

* Develop custom data models and algorithms to apply to data sets.

* Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.

* Coordinate with different functional teams to implement models and monitor outcomes.

* Develop processes and tools to monitor and analyze model performance and data accuracy.

Skills :

* Strong problem solving skills with an emphasis on product development.

* Hands on well versed with MySQL and Oracle database (NoSQL database knowledge is a plus)

* Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.

* Experience working with and creating data architectures.

* Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

* Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

* Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, Real time streaming across various databases etc.

* Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, shiny, tableau etc. - Mandate

* Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc. will be a plus

* Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.

* Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.

* Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.