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Senior Data Scientist

Arena

New York, NY, US

Posted about 3 years ago

Using data and predictive analytics to transform health care organizations.

Tech stack

  • SQL

We are a small, early stage, high growth company focused on using data science to transform the way people are hired. We seek an inventive, collaborative, methodologically-grounded, experienced, socially-minded data scientist to join our team. Reporting to the Vice President of Data Science, this individual will lead the exploration of applicant and employee data streams that Arena collects and pioneer new development of machine learning and AI methods suited for that data. He/she will also work closely with Arena’s Engineering and Product teams to ensure the successful implementation and refinement of such methods.

Mission and culture

At Arena our mission is simple: use data to transform the workforce such that people and organizations thrive. If you ask anyone at Arena about our company culture the first word you’ll probably hear is collaborative. While it’s true the people here are all intelligent, hardworking, and capable, we are also people who are open to criticism and check our egos at the door. We are charting new territory, and empathy and humility are critically important to our journey.

This is just the beginning of a revolution in how employers use data to make better HR decisions and how individuals are able to find fulfilling work beyond the bounds of bias. 

We enjoy substantial funding and are building out our team as we gain market share.

What We Believe In:

  • Empathy with one another and our users. Inclusiveness, communication and collaboration are core tenets of how we work.
  • Contribution to the open source community. We are built on open source technologies and we give back. 💻
  • Small feedback loops are critical to developing product and technology.
  • Ownership gives individuals the agency to grow and aligns outcomes. 📈

Responsibilities:

  • Develop innovative solutions to business, product or technical requests using appropriate Data Science techniques. 🧠
  • Prototype solutions using appropriate machine learning or statistical models and techniques; assist the engineering team in implementing such solutions 📊
  • Review existing processes, approaches, and models related to data science; propose and initiate solutions and/or improvements
  • Disseminate knowledge and techniques; solidify best practices by contributing to internal tools or libraries; mentor junior data scientists 🤯
  • Contribute code and documentation to the company code/knowledge base

Requirements:

  • 3+ years practical experience in industry product as a Data Scientist in a production environment
  • Excellent Python (numpy, pandas, scikit-learn, etc.) or R programming skills, familiar with open source libraries and tools for data science
  • Track record of speedily and rigorously developing and deploying machine learning models to resolve industry problems
  • Strong SQL skills
  • Superior communication and data visualization skills
  • Experience working in an agile development environment

Bonus Skills:

  • Master’s or PhD in a quantitative field (such as computer science, statistics, a quantitative social, biological, or physical science) is preferred but not required
  • Experience with Natural Language Processing, deep learning, experimental design and A/B testing, recommended systems or other deployed data products
  • Experience working in software development
  • Experience with sophisticated statistical or econometrical models.

Perks:

  • The mission, the people and the work. 🚀
  • The mission: work on a project that is making the world a better place. 🌎
  • The people: work for a high growth company, and learn in an environment where people care about growth and work/life balance.
  • The work: pragmatically use amazing technology.
  • Competitive salary, benefits and equity.

Compensation

$100K - 175K + Equity

Role type

Full time

Visa sponsorship

Not provided

Benefits & perks

  • Flexible Working

  • Health Insurance

  • Equity

  • 401(K)

  • 401K

  • Health care

  • Gym membership

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