Data Scientist - SQL/Python (5-10 yrs)
Role & 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.
- Develop company A/B testing framework and test model quality.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy as well as consistency in the IPL program.
Required Skill sets:
- Strong problem-solving skills with an emphasis on product/service development.
- Experience using statistical computer languages (R, Python, SQL, 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.
- Excellent written and verbal communication skills for coordinating across teams.
- A drive to learn and master new technologies and techniques.
- We're looking for someone with 5-7 years of experience manipulating data sets and building statistical models, has a Master's or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
- Knowledge and experience in statistical and data mining techniques; GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
- Experience querying databases and using statistical computer languages; R, Python, SQL, 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.
- Experience analyzing data from 3rd party providers; Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
- Experience with distributed data/computing tools; Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
- Experience visualizing/presenting data for stakeholders using; Periscope, Business Objects, D3, ggplot, etc