Data Scientist II
Company Name: Comcast
Location: New York, NYC
Date Posted: 23rd Jun, 2017
- Diving into huge, noisy, and complex real-world behavioral data to produce innovative analysis and new types of predictive models of customer behaviors and video product performance
- Appling your extensive experience in data architecture and management to building big data foundation and the data science infrastructure for video content and viewing behavior analytics.
- Unleashing your creativity to find hidden gems that improve our understanding video content consumption that will drive actionable business decisions
- Collaborating with teammates to solve business problems using broad spectrum of data science tools, packages and visualization techniques.
- Builds analytical models using statistical, machine learning and data mining methodologies.
- Applies cleansing, discretization, imputation, selection, generalization etc. to create high quality features for the modeling process.
- Executes standard exploratory and ad hoc data analysis. Interprets and presents results using tools such as Tableau, Excel, etc.
- Designs and implements big data architecture that serves as the foundation for video content and viewing behavior analytical platform
- Utilizes Hadoop, SQL and NoSQL languages, tools and technologies to extract and process data for analytical needs. Architects and develops data processing pipelines.
- Collaborates with software development teams to operationalize analytical solutions and create analytical/business intelligence products.
- Participates in the analysis and formalization of business problems. Implements and evaluates business metrics.
- Consistent exercise of independent judgment and discretion in matters of significance.
- Regular, consistent and punctual attendance. Must be able to work variable schedule if necessary.
- Other duties and responsibilities as assigned.
- Knowledge of machine learning, data mining and natural language processing algorithms with exposure to advanced algorithms like neural networks, SVM, random forests, bagging, gradient boosting machines, k-means++, etc.
- Solid background and practical experience in relational and non-relational databases, data architecting, data management and complex data processing in traditional and big data ecosystems. Experience with TVset-top box data and/or digital video data is a plus.
- Knowledge of at least one of the analytics languages/toolkits such as R, SAS, SPSS, Matlab or Python with analytical extensions.
- Knowledge of at least one programming/scripting language like Python, Scala, Julia, Ruby, or Java, C#, etc. is preferred.
- Proficiency working within the Hadoop platform including Kafka, Spark, Hbase, Impala, Hive, and HDFS in multi-tenant environments
Educational Level And Experience
- Advanced degree in Computer Science, Applied Mathematics, Statistics, Econometrics, Quantitative Social Sciences or related field.
- At least 3-5 years of experience depend on educational level and relevance