Data Scientist Machine Learning at Underdog Sports

What is Underdog?
Founded by a team of industry veterans, Underdog was born with the idea that bringing strategic innovation to sports gaming and entertainment is the key to success in an exceptionally competitive market. Underdog has quickly established itself as a leader in the space, and is committed to building the best sports gaming platform in the industry -- and supporting the most passionate community of sports fans while doing it!
At Underdog, we’re not only about creating these awesome products, but also about growing our culture of passion, ownership, and fun! We believe that great companies are made out of great people. Our continual aim is to create an inclusive environment for everyone, at all levels, to achieve their highest potential at work.
We are looking for intellectually curious, highly motivated individuals to be the foundational members of our Machine Learning Data Science team. As a Machine Learning Data scientist at Underdog, you’ll be building out the next-gen AI powered gaming platform that will lead the sports gaming industry. You will be part of a team whose focus is to solve cutting edge data science problems and deploy state-of-the-art models.
You will develop models, systems and features that leverage the massive scale of Underdog’s user base to understand and predict user behavior, and to optimize the experience at all stages of the user journey. You will engage in and manage an end-to-end machine learning (ML) development lifecycle from data, use case, solution design and modeling to production deployment and monitoring. 
Projects can range from working on a wide-variety of statistical and machine learning problems, e.g. experiment design (AB testing), causal inference, clustering, propensity modeling, survival models, classification and regression modeling, pricing, fraud/anomaly detection, MCMC, Bayesian models.
*Please note, Underdog is a US based company and no sponsorship is available for this position at this time. 
What you’ll do:

Design, explore, build, evaluate, deploy and iterate on statistical/ML models
Build across the entire machine learning development process to implement ML algorithms in production, including exploratory data analysis, data modeling, feature engineering, model training and tuning, testing, deployment, and monitoring
Design experiments/AB tests, analyze/interpret results and communicate insights to leadership and stakeholders 
Work with large scale data systems, build large scale training and inference pipelines
Work with Product, Design, Infra and Frontend teams to bring your models, and features to life
Partner closely across the business to identify improvements and opportunities, influence decisions using data science

Who you are:

BS, MS, or PhD in Statistics, Mathematics, Economics, Operations Research, Computer Science, or other quantitative fields or related academic/work experience
3+ years of experience building and deploying statistical/ML models 
Industry experience working with large scale data
Strong analytical and problem-solving skills, thrive in ambiguous environments and get excited about figuring out solutions to complex problems, and then executing on them
Ability to work autonomously and lead initiatives across multiple product areas and communicate findings with leadership and product teams
Proven machine learning and software engineering skills across languages including Python, R etc.
Experience with ML software tools and libraries (e.g., Scikit-learn, Keras, statsmodels, PyTorch, Huggingface, Haystack, Fastai, TensorFlow, Nvidia, Nbdev.)

Even better if you have…

MS, PhD in Statistics or related field with research in machine learning
Familiarity with large-scale data processing and distributed systems
Experience with MLOps pipelines 
Experience with one or more of the following: deep learning, natural language processing, computer vision, bayesian reasoning, recommendation systems, search and ranking, learning from semistructured data, graph learning, reinforcement or active learning, ML software systems, machine learning on mobile devices

 
Underdog Sports is firmly committed to equity, inclusion, and diversity. Our unique culture was built on the foundation of a safe and inclusive environment for people of all backgrounds. We highly value the mental, physical, and emotional health of our employees, and are continuously asking ourselves: what can we do better? Underdog is an equal opportunity employer and doesn't discriminate on the basis of creed, race, sexual orientation, gender, age, disability status or any other defining characteristic. Our targeted compensation rate for this position is between $140,000 and $185,000, depending on experience, plus equity. Think your skills are exceptional and warrant higher pay? Apply anyway! If we agree, we're willing to negotiate. Below you’ll find a few of our perks:

Unlimited PTO (we're extremely flexible with the exception of the first few weeks before & into the NFL season)
16 weeks of fully paid parental leave
Company paid Health, Dental, Vision plan option for employees and dependents
401k Match & FSA
Remote, In-Person, or Hybrid Scheduling – we are 100% VIRTUAL FIRST!
A $500 home office allowance
$100 in UD credit
Support for learning and development
Book club – expense your books!
Monthly raffle to win a sports ticket reimbursement of up to $500 (including game day snacks!)
Lastly, an extremely transparent, fun, and engaging culture where you will grow both personally and professionally!

 
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