Data Scientist
Swish Analytics San Francisco, CA, US $75k – $120k Long term Middle
Flexible Hours
Health Insurance
About Swish Analytics

Swish Engineering is a high-performance team focused on pioneering the next generation of predictive analytics sports data products. We're looking for team players with authentic passion for accurate predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our engineering challenges are unique, so you should be comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.

Job Description

As a member of our data science/machine-learning team, you'll have a direct impact on the infrastructure and delivery of our core consumer and enterprise data offerings. Our team is continually delivering the most innovative sports prediction analytics products in the consumer and enterprise marketplaces for new content creation, gamification, fantasy sports and sports betting experiences. 

Working in-office at our San Francisco HQ is mandatory. If you are interested, please send us an email with a cover letter, resume and information about why you're an ideal candidate.

Just some of the things you'll work on:

  • Architect low-latency real-time analytics systems including raw data collection, model development and endpoint production.
  • Build new sports betting data products and predictions offerings.
  • Integrate large and complex real-time datasets into new consumer and enterprise products.
  • Develop production-level predictive analytics into enterprise-grade APIs.
  • Contribute to the design and implementation of new automated sports data delivery framework.

Perks:

  • Ground floor opportunity with the team; shape the strategic direction of the company.
  • Work with an extremely passionate and fun group of people in a truly team-centric environment. We love amazing products, accurate data, quality predictions, sports and betting. Whether you're our star player or you come off the bench to close out the game, we all cheer for one another.
  • The rare opportunity to pioneer a new era of data analytics in a massive and rapidly-growing industry.
  • A casual, flexible and exciting work enviroment.

Benefits:

  • Extremely competitive base salary.
  • Opportunity to earn equity.
  • Full medical/dental/vision package to fit your needs.
  • Ability to work remotely on an as-need basis.
  • Unlimited vacation policy. Work hard, execute, and take time as you need it.

Requirements

The kinds of skills we're looking for:

  • Passion for accurate predictions and real-time data. We're looking for software engineers who find true joy and satisfaction in building pioneering products with the latest and greatest predictive data technologies.
  • Team player, comfortable leading. You understand the value and advantage of an entire team working in unison towards a common goal. You rely on candid feedback for continuous improvement and are comfortable leading others into uncharted technical territory.
  • Fast learner. We're looking for software engineers who thrive on learning new technologies and adapt easily to meet the needs of our rapidly evolving product suite and industry environment.
  • Versatility. Strong machine-learning chops. You know how to build scalable, robust, and fault-tolerant systems that support our constantly-evolving data requirements. You are able to quickly assess project scope and identify the most efficient solutions without compromising accuracy, latency or quality.
  • Work ethic and fearlessness. You pride yourself on diving into new challenges. You love getting your hands dirty and understand that failure is sometimes the only route to finding the best solutions.

Technical specifics:

  • B.A./B.S. in Mathematics, Computer Science, or related STEM field.
  • Proficiency in Python (scikit-learn, pandas, NumPy, SciPy) (2-4 years)
  • Expertise in database management, preferably SQL (2-4 years)
  • Experience with NoSql databases (Cassandra, MongoDb) (1-2 years)
  • Strong background in applying machine learning techniques to real-world problems, including feature engineering, algorithm derivation and selection, and performance tuning
  • Understanding of probability theory and inferential statistics
  • Knowledge of version control (git), shell scripting, and cloud-computing infrastructures (Amazon Web Services) (1-2 years)
  • Experience with web scraping and cleaning unstructured data
  • Experience with Distributed Computing
  • Experience building low-latency, scalable data pipelines and applying appropriate technologies and frameworks (Kafka, Amazon SQS, Hadoop, Spark, Storm, Spark Streaming, MapReduce)

Bonus points:

  • Several projects on github that illustrate experience in the requirements above
  • Phd or MS in related field
  • Familiarity with “Big Data” technologies (Hadoop, Spark)
  • Familiarity with a Neural Network framework (TensorFlow, Caffe, Theano, Keras) or with building NLP solutions
  • Experience writing production level code
  • Experience working with time series or sports data

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