Data Scientist II
Responsible for leveraging internal and external data to provide insights and information which supports a facts-based decision making process. Provides input into strategy, analysis methods, and tool selection. Works independently with minimal-to-no supervision while also demonstrating the ability to lead projects and initiatives autonomously.
- Uses analytical rigor and statistical methods to analyze large amounts of data, extracting actionable insights using advanced statistical techniques such as data analysis, data mining, optimization tools, and machine learning techniques and statistics (e.g., predictive models, LTV, propensity models).
- Develops and executes statistical and mathematical solutions to business problems to support larger initiatives under the direction of senior team members.
- Produce analysis of historical patterns in customer behaviors and product performance from complex real-world behavioral data.
- Develop and deploy predictive models based on historical data that provide future predictions about customer behavior.
- Constructs forecasts, recommendations and strategic/tactical plans based on applying data science techniques to business data.
- Create deliverables and presentations that report methodology and results of analysis.
- Build customer centric models and optimization tools to support large scale projects that utilize online & offline data, structured & unstructured data, set top box data, and media/behavioral/attitudinal data.
Education Level:Master's degree
Field of Study:Economics, Statistics, Mathematics, Decision Science, Operational Research, Computer Science, Engineering or related field
Years of Experience:Generally requires 2-5 years related experience.
- PhD preferred
- Experience with statistical modeling techniques such as regression, decision trees, neural networks, support vector machines, clustering techniques.
- Ability to develop statistical targeting models using SAS, R, Python, Weka, SPSS, MATLAB, etc.
- Understanding or experience working within an enterprise data warehouse environment, (including SQL, procedural SQL, and ETL) in a relational environments and MPP platforms (Teradata, Netezza, Oracle, etc.)
- Experience with distributed computing platforms, such as Hadoop, and associated technologies such as MapReduce, Spark, Yarn, and Hive
- Experience with at least 1 programming language such as Python, Scala, Julia, Java, C++, etc.
Compliance:Comcast is an EEO/AA/Drug Free Workplace.
Disclaimer:The above information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.
Comcast is an EOE/Veterans/Disabled/LGBT employer