Senior Data Scientist

Fanatics Commerce•New York, NY

1d•$194,940 - $214,940•Hybrid

About The Position

Fanatics Commerce is the global leader in licensed sports merchandise, operating a vertically integrated platform that designs, manufactures, and delivers officially licensed apparel, jerseys, headwear, and collectibles for major leagues, teams, and events worldwide. With more than 900 e-commerce sites and a global omnichannel presence across digital, in-venue, and retail, Fanatics Commerce reaches fans in over 180 countries and powers official fan experiences for many of the world's iconic sports properties. At Fanatics, we bring our BOLD Leadership Principles to life every day - building championship teams, obsessing over fans, acting with entrepreneurial speed, and delivering with a determined and relentless mindset. Build and train machine learning models for customer marketing purposes (CRM, ad bidding, etc.) (25%): Define the dataset used for the model; Determine the model architecture (xgboost, regression, etc.); Create the train/test/score pipeline. Deploy models into production at scale (25%): Create docker images for models; Put containers in appropriate artifact stores; Create DAGs to run pipelines. Conduct exploratory analysis to understand how the business is run and how to model it (25%): Identify potential opportunities to drive revenue and contribution growth and lead projects to evaluate them; Utilize a wide range of data science capabilities from exploratory analysis and modeling, to creating reports and dashboards, and A/B testing; Identify any new data capture required and build custom data sets to enable reports of novel features and processes; Load and join data from multiple locations; Aggregate, filter, and summarize data; Create plots and presentations from the data. Communicate with business partners to align business goals with science techniques and report results outward (25%): Define requirements from stakeholders and explicitly define the business problem; Apply innovative problem-solving skills to dissect data and build machine learning / statistical models to solve business problems from different perspectives; Determine the data science techniques that align with those problems; Use strong communication skills (written and verbal) to report on results and communicate with the business to understand if the problem is solved. Up to 5% domestic travel may be required for meetings. Partial telecommuting permitted; onsite at 95 Morton Street, New York, NY 10014 when not telecommuting. Salary: $194,940 - $214,940 per year.

Requirements

Bachelor’s degree or U.S. equivalent in Computer Science, Marketing Analytics, Data Analytics, Statistics, or related field
4 years of professional experience as a Data Scientist, Data Analyst, or any occupation, job title, or position creating machine learning models to use in production systems or to generate insights for businesses
3 years of professional experience developing and training machine learning models using data science techniques including XGBoost, regressions, hyper-parameter tuning, and feature selection to support customer marketing initiatives including CRM
3 years of professional experience building end-to-end machine learning pipelines including data definition, and train/test splits
3 years of professional experience performing exploratory data analysis by loading, joining, aggregating, filtering, and visualizing data from multiple sources
3 years of professional experience continuously running a model in production
3 years of professional experience collaborating with marketing and other partner teams to define business problems, gather stakeholder requirements, and align modeling approaches with strategic goals
3 years of professional experience translating complex data science outcomes into actionable insights for non-technical audiences
3 years of professional experience determining and applying data science techniques (including customer segmentation and lifetime value models) to solve clearly defined business problems in a marketing context
3 years of professional experience writing code in Python and R and running data science tasks in managed cloud environments including AWS

Responsibilities

Build and train machine learning models for customer marketing purposes (CRM, ad bidding, etc.)
Define the dataset used for the model
Determine the model architecture (xgboost, regression, etc.)
Create the train/test/score pipeline
Deploy models into production at scale
Create docker images for models
Put containers in appropriate artifact stores
Create DAGs to run pipelines
Conduct exploratory analysis to understand how the business is run and how to model it
Identify potential opportunities to drive revenue and contribution growth and lead projects to evaluate them
Utilize a wide range of data science capabilities from exploratory analysis and modeling, to creating reports and dashboards, and A/B testing
Identify any new data capture required and build custom data sets to enable reports of novel features and processes
Load and join data from multiple locations
Aggregate, filter, and summarize data
Create plots and presentations from the data
Communicate with business partners to align business goals with science techniques and report results outward
Define requirements from stakeholders and explicitly define the business problem
Apply innovative problem-solving skills to dissect data and build machine learning / statistical models to solve business problems from different perspectives
Determine the data science techniques that align with those problems
Use strong communication skills (written and verbal) to report on results and communicate with the business to understand if the problem is solved