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 data 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

Data

Basic Qualifications

* Demonstrated ability to present data science results and recommendations to business and technical clients.
* 3+ years of experience as a Data Scientist in technology sector.
* 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).
* Experience with deep learning, NLP, Neural Networks, and/or Bayesian modeling.
* Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick effective solutions as appropriate

Business

Disney Streaming Services

Required Education

* Graduate degree with background in statistics or machine learning.

Postal Code

10011

Responsibilities

* Reframe objectives as machine learning tasks that can deliver actionable insights, accurate predictions, and effective optimization.
* Implement and execute machine learning with reliability and reproducibility.
* Explain how models and systems work to both non-technical and technical stakeholders.
* Collaborate with engineering teams to build data-based products and help integrate into the products and operational processes.
* Process, cleanse, and verify the integrity of data used for analysis.
* 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.

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 data 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

* Demonstrated ability to present data science results and recommendations to business and technical clients.
* 3+ years of experience as a Data Scientist in technology sector.
* 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).
* Experience with deep learning, NLP, Neural Networks, and/or Bayesian modeling.
* Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick effective solutions as appropriate

Required Education

* Graduate degree with background in statistics or machine learning.

Responsibilities

* Reframe objectives as machine learning tasks that can deliver actionable insights, accurate predictions, and effective optimization.
* Implement and execute machine learning with reliability and reproducibility.
* Explain how models and systems work to both non-technical and technical stakeholders.
* Collaborate with engineering teams to build data-based products and help integrate into the products and operational processes.
* Process, cleanse, and verify the integrity of data used for analysis.
* 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.