Disney Direct to Consumer
Lead Data Scientist
Disney Direct to Consumer, San Francisco, California, United States, 94102
Data
Scientists at Direct to Consumer
are the insights and modeling partners for the growth, content, marketing, product, and engineering teams at Disney+,
Hulu
and ESPN+. They use data to empower decision-makers with information, predictions, and insights that
ultimately influence
the experiences of millions of users worldwide. Scientists on the team build models, perform statistical analysis, and create visualizations to provide scalable, persistent capability that is iteratively improved through direct interaction with cross-functional business partners.
As a
L
ead
D
ata
S
cientist in the DTC (Direct-To-Consumer) Data Science team, you will be partnering closely with the Marketing, Subscriber Analytics, Finance, Business Operations, Commerce Product and Engineering teams to develop models for tackling a multitude of exciting challenges, including content/audience segmentation, customer lifetime value estimation, churn and upgrade prediction, signups and subscribers forecasting, fraud prevention and mitigation, payment optimization, causal inference, anomaly detection and much more! In this role you will also be working very closely with company
executives
and it requires the use of analytical abilities, business understanding, and technical savviness to identify specific and actionable opportunities to solve existing business problems through data modeling.
We are looking for someone with deep analytical and modeling
expertise
, a proven
track record
of thought leadership and eagerness to drive impact.
Responsibilities
Modeling
: Design, build and improve machine learning models. Work end to end from data collection, feature generation and selection, algorithm development, forecasting, visualization and communicating of model results. Collaborate with engineering to
productionize
models. Drive experimentation to test impact of
model based
optimization.
Deep analysis
: Develop comprehensive understanding of subscriber and payment data structures and metrics. Mine large data sets to
identify
opportunities for driving growth and retention of subscribers.
Visualization of Complex Data sets
: Development of prototype solutions, mathematical models, algorithms, and robust analytics leading to actionable insights communicated clearly and visually.
Partnership
: Partner closely with business stakeholders to
identify
and unlock opportunities, and with other data teams to improve platform capabilities around data modeling, data visualization,
experimentation
and data architecture.
Basic Qualifications
Bachelor’
s
in
Advanced Mathematics
, Statistics, Data
Science
or comparable field of study.
7+ years of experience designing, building, and evaluating practical machine learning solutions
Strong coding experience in one (or more) data programming languages like Python/R,
additional
experience with scientific libraries like
Numpy
, Pandas, or equivalent libraries a plus.
Strong background in statistical modeling: regression, time series analysis and other techniques.
Experience developing scalable mathematical models and solving complex quantitative problems that can be understood by non-mathematical colleagues.
7+
years experience
with databases and data pulling tools (SQL, Vertica, Hive).
Willingness to adapt in
fast
-paced and quickly growing work environment.
Seasoned & resourceful problem solver who figures out how to get things done, even if it means navigating through ambiguity
Preferred Qualifications
Advanced degree (
Master’s
or
Ph.D.) in a quantitative discipline
Excellent analytical skills, advanced level of statistics knowledge
Strong
expertise
with Python and libraries such as scikit-learn,
scipy
*
Familiarity with Bayesian modeling and probabilistic programming packages such as
PyMC
Familiarity with data platforms and applications such as Databricks,
Jupyter
, Snowflake, Airflow,
Github
Familiarity with data exploration and data visualization tools such as Tableau, Looker
Familiarity with designing and analyzing A/B testing and other experiment types
Demonstrated skills in selecting the right statistical tools given a data analysis problem
Ability to adapt quickly in a fast-moving environment with shifting priorities
Strong communication
skills, for both technical and non-technical audiences
Ability to handle multiple tasks concurrently and
in a timely manner
, including large and complex ones
Demonstrated leadership experience, including people and project management
Experience in advanced ML techniques (neural nets, NLP, image processing)
Experience thinking strategically to interpret market and consumer information, preferably about a subscription service.
Additional Information
#DISNEYTECH
The hiring range for this position in New York, NY is $159,500 to $213,900 per year and in Santa Monica, CA is $152,200 to $204,100. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial and/or other benefits, dependent on the level and position offered.
Scientists at Direct to Consumer
are the insights and modeling partners for the growth, content, marketing, product, and engineering teams at Disney+,
Hulu
and ESPN+. They use data to empower decision-makers with information, predictions, and insights that
ultimately influence
the experiences of millions of users worldwide. Scientists on the team build models, perform statistical analysis, and create visualizations to provide scalable, persistent capability that is iteratively improved through direct interaction with cross-functional business partners.
As a
L
ead
D
ata
S
cientist in the DTC (Direct-To-Consumer) Data Science team, you will be partnering closely with the Marketing, Subscriber Analytics, Finance, Business Operations, Commerce Product and Engineering teams to develop models for tackling a multitude of exciting challenges, including content/audience segmentation, customer lifetime value estimation, churn and upgrade prediction, signups and subscribers forecasting, fraud prevention and mitigation, payment optimization, causal inference, anomaly detection and much more! In this role you will also be working very closely with company
executives
and it requires the use of analytical abilities, business understanding, and technical savviness to identify specific and actionable opportunities to solve existing business problems through data modeling.
We are looking for someone with deep analytical and modeling
expertise
, a proven
track record
of thought leadership and eagerness to drive impact.
Responsibilities
Modeling
: Design, build and improve machine learning models. Work end to end from data collection, feature generation and selection, algorithm development, forecasting, visualization and communicating of model results. Collaborate with engineering to
productionize
models. Drive experimentation to test impact of
model based
optimization.
Deep analysis
: Develop comprehensive understanding of subscriber and payment data structures and metrics. Mine large data sets to
identify
opportunities for driving growth and retention of subscribers.
Visualization of Complex Data sets
: Development of prototype solutions, mathematical models, algorithms, and robust analytics leading to actionable insights communicated clearly and visually.
Partnership
: Partner closely with business stakeholders to
identify
and unlock opportunities, and with other data teams to improve platform capabilities around data modeling, data visualization,
experimentation
and data architecture.
Basic Qualifications
Bachelor’
s
in
Advanced Mathematics
, Statistics, Data
Science
or comparable field of study.
7+ years of experience designing, building, and evaluating practical machine learning solutions
Strong coding experience in one (or more) data programming languages like Python/R,
additional
experience with scientific libraries like
Numpy
, Pandas, or equivalent libraries a plus.
Strong background in statistical modeling: regression, time series analysis and other techniques.
Experience developing scalable mathematical models and solving complex quantitative problems that can be understood by non-mathematical colleagues.
7+
years experience
with databases and data pulling tools (SQL, Vertica, Hive).
Willingness to adapt in
fast
-paced and quickly growing work environment.
Seasoned & resourceful problem solver who figures out how to get things done, even if it means navigating through ambiguity
Preferred Qualifications
Advanced degree (
Master’s
or
Ph.D.) in a quantitative discipline
Excellent analytical skills, advanced level of statistics knowledge
Strong
expertise
with Python and libraries such as scikit-learn,
scipy
*
Familiarity with Bayesian modeling and probabilistic programming packages such as
PyMC
Familiarity with data platforms and applications such as Databricks,
Jupyter
, Snowflake, Airflow,
Github
Familiarity with data exploration and data visualization tools such as Tableau, Looker
Familiarity with designing and analyzing A/B testing and other experiment types
Demonstrated skills in selecting the right statistical tools given a data analysis problem
Ability to adapt quickly in a fast-moving environment with shifting priorities
Strong communication
skills, for both technical and non-technical audiences
Ability to handle multiple tasks concurrently and
in a timely manner
, including large and complex ones
Demonstrated leadership experience, including people and project management
Experience in advanced ML techniques (neural nets, NLP, image processing)
Experience thinking strategically to interpret market and consumer information, preferably about a subscription service.
Additional Information
#DISNEYTECH
The hiring range for this position in New York, NY is $159,500 to $213,900 per year and in Santa Monica, CA is $152,200 to $204,100. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial and/or other benefits, dependent on the level and position offered.