Data Scientist (Media Domain Exp)

Job description

Role Details

We are looking for an enthusiastic data science contractor to improve our machine learning products to optimize content and marketing investment decisions You will support our existing suite of subscriber propensity and content forecasting models by leveraging datasets collected from tens of millions of users as they engage with content on Paramount These models will enable you to create user or contentlevel insights and forecasts to guide P Finance and Marketing decisions An ideal candidate would be someone with a track record of building and deploying models excellent communication skills and interest in the streaming entertainment industry

Your DaytoDay

Design implement optimize and maintain machine learning models to predict content performance

Build and deploy endtoend ML pipelines that can handle largescale data efficiently

Continuously monitor model performance in production via automation and iterate to maintain relevance

Experiment with novel methods to improve forecasting accuracy and interpretability

Work closely with other data scientists business intelligence finance and content teams for any adhoc forecasting needs

Validate models through backtesting and evaluation of observed data

Deliver data insights at the appropriate level of detail and perform fast followup to feedback

Qualifications

You Have 2 years experience in Data Science and ML Engineering

MS or PhD in StatisticsData ScienceComputer Science or related disciplines with specialization in machine learning techniques

Knowledge of both supervised and unsupervised machine learning techniques

Have full stack experience in data collection aggregation analysis visualization productionalization and monitoring of data science products

The ability to write robust code in Python and leverage associated machine learning packages

Experience using Jupyter Notebooks

Familiarity with a variety of statistical models and methods ie causal methods treebased algorithms time series analysis regression analysis

Communicate concisely and persuasively with engineers and product managers

Strong detail orientation with a penchant for data accuracy

Familiar with version control systems Git BitBucket

Must successfully pass a background check

You might also have

Experience using Google Cloud Platform BigQuery ML Engine and APIs

Experience using project management tools like those from Atlassian JIRA Confluence

Can wrangle data using SQL and Pandas

Background in NLP or text mining techniques is a plus

Job description

Role Details

We are looking for an enthusiastic data science contractor to improve our machine learning products to optimize content and marketing investment decisions You will support our existing suite of subscriber propensity and content forecasting models by leveraging datasets collected from tens of millions of users as they engage with content on Paramount These models will enable you to create user or contentlevel insights and forecasts to guide P Finance and Marketing decisions An ideal candidate would be someone with a track record of building and deploying models excellent communication skills and interest in the streaming entertainment industry

Your DaytoDay

Design implement optimize and maintain machine learning models to predict content performance

Build and deploy endtoend ML pipelines that can handle largescale data efficiently

Continuously monitor model performance in production via automation and iterate to maintain relevance

Experiment with novel methods to improve forecasting accuracy and interpretability

Work closely with other data scientists business intelligence finance and content teams for any adhoc forecasting needs

Validate models through backtesting and evaluation of observed data

Deliver data insights at the appropriate level of detail and perform fast followup to feedback

Qualifications

You Have 2 years experience in Data Science and ML Engineering

MS or PhD in StatisticsData ScienceComputer Science or related disciplines with specialization in machine learning techniques

Knowledge of both supervised and unsupervised machine learning techniques

Have full stack experience in data collection aggregation analysis visualization productionalization and monitoring of data science products

The ability to write robust code in Python and leverage associated machine learning packages

Experience using Jupyter Notebooks

Familiarity with a variety of statistical models and methods ie causal methods treebased algorithms time series analysis regression analysis

Communicate concisely and persuasively with engineers and product managers

Strong detail orientation with a penchant for data accuracy

Familiar with version control systems Git BitBucket

Must successfully pass a background check

You might also have

Experience using Google Cloud Platform BigQuery ML Engine and APIs

Experience using project management tools like those from Atlassian JIRA Confluence

Can wrangle data using SQL and Pandas

Background in NLP or text mining techniques is a plus