Data Scientist
New York, NY

Job Description

Job Description

The Data Scientist is a critical position within DSS and in the Data organization who specializes in applying machine learning methods to meet optimization, personalization, recommendations and efficiency related challenges, in close collaboration with engineering and business partners. In this role, you will build and apply machine learning techniques and modern statistics to marketing data to both augment decision-making but to also significantly improve operational process problems through automation. You will collaborate across teams to define problems and develop automated solutions with the Data, Product and Engineering teams to be built into our products.

Job Type

Full Time

Segment

Direct-to-Consumer and International

Category

Technology

Basic Qualifications

* 5+ years of relevant experience in Data Science
* Demonstrated delivery of machine learning techniques in real-time applications.
* Expertise in modern statistics/data science/machine learning.
* Expertise in a statistical programming language (we use Python and R internally) and data access tools (e.g., SQL).
* The candidate must have a sufficient understanding of and practical experience with classic statistical modeling techniques (e.g., logistic regression, CART, K-means clustering) and machine learning algorithms (e.g., gradient boosting, neural networks, random forest, etc.).
* Comfort with large, ambiguous streams of data across different formats and entry points; Hands-on experience processing large datasets; hands on experience with cloud environments (e.g., AWS, Snowflake and Big Data technologies (e.g. Hadoop, Spark)
* Experience developing high value features; Hands-on experience deploying models in real-time environments
* Demonstrated ability to present data science results and recommendations to business and technical clients.

Business

Disney Streaming Services

Required Education

* Bachelor's degree in relevant focus (i.e., Computer Science, Data Science, Statistics or Machine Learning);

Preferred Qualifications

Working within the Marketing/Advertising vertical is a plus.

Postal Code

10011

Preferred Education

* Graduate degree highly preferred.

Responsibilities

* Lead Data Science deliverables for the Marketing Acquisition team by delivering actionable analysis, models, data products and other ongoing innovation initiatives to improve marketing efficiency.
* Consult with teams to provide and execute analytical solutions to solve complex business questions and deliver better insights specifically related to return on marketing investment.
* Collaborate with and build relationships within Marketing, Engineering, Data Science, and Analytics teams to build data-based products and help integrate into the products and operational processes.
* Collaborate with Analytics and Marketing team to design tests to showcase the power of good measurement using client data and Facebook or third-party technology tools
* Explore and help rollout multi-touch attribution models for DSS's subscription businesses.
* Establish affinity and propensity models to refine campaign audience selection.
* Enhance data collection procedures to include information that is relevant for creating better ML models.
* Create automated anomaly detection systems and constant tracking of its performance.
* Increase internal adoption of advanced analytics methods including machine learning.
* Present findings in a way that addresses not only the interpretation of the statistical results, but the business implications of the contributing analysis.

Job Description

The Data Scientist is a critical position within DSS and in the Data organization who specializes in applying machine learning methods to meet optimization, personalization, recommendations and efficiency related challenges, in close collaboration with engineering and business partners. In this role, you will build and apply machine learning techniques and modern statistics to marketing data to both augment decision-making but to also significantly improve operational process problems through automation. You will collaborate across teams to define problems and develop automated solutions with the Data, Product and Engineering teams to be built into our products.

Basic Qualifications

* 5+ years of relevant experience in Data Science
* Demonstrated delivery of machine learning techniques in real-time applications.
* Expertise in modern statistics/data science/machine learning.
* Expertise in a statistical programming language (we use Python and R internally) and data access tools (e.g., SQL).
* The candidate must have a sufficient understanding of and practical experience with classic statistical modeling techniques (e.g., logistic regression, CART, K-means clustering) and machine learning algorithms (e.g., gradient boosting, neural networks, random forest, etc.).
* Comfort with large, ambiguous streams of data across different formats and entry points; Hands-on experience processing large datasets; hands on experience with cloud environments (e.g., AWS, Snowflake and Big Data technologies (e.g. Hadoop, Spark)
* Experience developing high value features; Hands-on experience deploying models in real-time environments
* Demonstrated ability to present data science results and recommendations to business and technical clients.

Required Education

* Bachelor's degree in relevant focus (i.e., Computer Science, Data Science, Statistics or Machine Learning);

Preferred Qualifications

Working within the Marketing/Advertising vertical is a plus.

Preferred Education

* Graduate degree highly preferred.

Responsibilities

* Lead Data Science deliverables for the Marketing Acquisition team by delivering actionable analysis, models, data products and other ongoing innovation initiatives to improve marketing efficiency.
* Consult with teams to provide and execute analytical solutions to solve complex business questions and deliver better insights specifically related to return on marketing investment.
* Collaborate with and build relationships within Marketing, Engineering, Data Science, and Analytics teams to build data-based products and help integrate into the products and operational processes.
* Collaborate with Analytics and Marketing team to design tests to showcase the power of good measurement using client data and Facebook or third-party technology tools
* Explore and help rollout multi-touch attribution models for DSS's subscription businesses.
* Establish affinity and propensity models to refine campaign audience selection.
* Enhance data collection procedures to include information that is relevant for creating better ML models.
* Create automated anomaly detection systems and constant tracking of its performance.
* Increase internal adoption of advanced analytics methods including machine learning.
* Present findings in a way that addresses not only the interpretation of the statistical results, but the business implications of the contributing analysis.