Experience: 10 – 18 years
Role: Data Scientist
- 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 or 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.
Qualifications For Data Scientist
- Strong problem solving skills with an emphasis on product development.
- Experience using statistical computer languages .R SAS 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 or 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 4-7 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 or tools:
- Coding knowledge and experience with several languages: C C++ Java
- Knowledge and experience in statistical and data mining techniques: GLM or Regression Random Forest Boosting Trees text mining social network analysis etc.
- Experience querying databases and using statistical computer languages: R SAS Python SLQ 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 or computing tools: Map or Reduce Hadoop Hive Spark Gurobi MySQL etc.