Machine Learning Engineer
San Francisco, CA
ViacomCBS Streaming (formerly CBS Interactive) is a division of ViacomCBS that encompasses both free, paid, and premium streaming services including Pluto TV, CBS All Access, CBS Sports Digital, and CBS News Digital.
The Data Engineer should possess a deep sense of curiosity and a passion for building smarter products based on data, and the ability to communicate data structures and tools throughout the CBS Digital Media organization. The perfect candidate for this role will use their skills in reverse engineering, analytics and creative experimental solutions to devise data and BI solutions. This engineer supports data pipeline development which includes machine learning algorithms using disparate data sources. The ideal candidate will also work BI, Research, Engineering and Product teams to implement data-driven plans that drive the business.
• Works with large volumes of traffic data and user behaviors to build pipelines that enhance raw data.
• Able to break down and communicate highly complex data problems into simple, feasible solutions.
• Extract patterns from large datasets and transform data into an informational advantage.
• Find answers to business questions via hands-on exploration of data sets via Jupyter, SQL, dashboards, statistical analysis, and data visualizations.
• Partnering with the internal product and business intelligence teams to determine the best approach around data ingestion, structure, and storage. Then, working with the team to ensure these are implemented correctly.
• Contributing ideas on how to make our data more effective and working with other members of the engineering, BI teams, and business units to implement changes.
• Ongoing development of technical solutions while developing and maintaining documentation, at times training impacted teams.
• Early on collaboration with the team on internal initiatives to create strategies that improve company processes.
What you bring to the team:
You have -
• Bachelor's degree and 2-4 years work experience in Analytics/Measurement/Data Operations fields or consulting roles with focus on digital analytics implementations.
• Experience with data management systems, both relational and NoSQL (e.g., HBase, Cassandra, MongoDB)
• Proficient in Python.
• Familiarity with SQL skills for MySQL, Postgres and BigQuery to perform common types of analysis
• Experience with exploratory data analysis using tools like iPython Notebook, Pandas & matplotlib, etc.
• Strong problem solving and creative-thinking skills.
• Ability to break down and communicate highly complex data problems as simple, feasible solutions
• Demonstrated development of ongoing technical solutions while designing and maintaining documentation, at times training impacted teams.
• Experience developing solutions to business requirements via hands-on discovery and exploration of data.
• Robust written and verbal communication skills, including the ability to communicate technical concepts to non-technical audiences, as well as translating business requirements into Data Solutions
• Experience with a Python web framework such as Django or Flask.
• Experience building and deploying application on a cloud platform (Google Cloud Platform preferred)
You might also have -
• Experience with Marketing tools like Kochava, Braze, Branch, Salesforce Marketing Cloud is a plus.
• Experience with Apache Airflow is a plus.
• Familiarity with Data Modeling.
• Familiarity in Hadoop pipelines using Spark, Kafka.
• Familiar with version control systems.
• Can perform statistical analyses using tools such as R, Numpy/SciPy with Python
• Experience with Adobe Analytics (Omniture) or Google Analytics.
• Digital marketing strategy including site, video, social media, SEM, SEO, and display advertising.
• Familiarity with ELT/ETL concepts
FUNCTION: Data and Research
Jobcode: Reference SBJ-g6z51j-3-238-173-209-42 in your application.
CBS Interactive is the premier online content network for information and online operations of ViacomCBS as well as some of the top native digital brands in the entertainment industry.