Head of Data Sciences
4 weeks ago
Things you need to have: Masters degree in Computer Science, Physics, Electrical Engineering, Statistics, or Mathematics, and 10+ years of related work experience OR a PhD and 8+ years of related work experience 4+ years of experience managing a team of technologists, data analysts, software engineers, and/or research scientists.
- Proficiency with an object oriented language (Java, C++) and a scripting language (Ruby, Python).
- Ability to develop system prototypes.
- Experience with statistical and mathematical libraries and software (R, Matlab, etc.)
- Strong experience developing robust automation solutions for distributed software systems.
- Excellent oral and written communication skills.
- Facility with standard machine learning techniques, error propagation, statistics, scientific thinking, and the ability to invent.
- A track record of thought leadership & contributions that have advanced the field.
- Ability to work collaboratively with both technical and non-technical stakeholders alike.
It would be great if you also had:
• Proficiency with relational databases and Linux
• Strong knowledge of agile processes
• Experience with modern methods for parallelized processing of large, distributed datasets (e.g. Hadoop, Map-reduce)
What you will be doing:
You will develop and apply rigorous mathematical and statistical models to semi-structured web data and deliver data-derived analytics services to millions of digital marketers, web publishers, and investors worldwide. You will mentor, coach, and manage a team of senior data analysts and software engineers and collaborate with senior leadership on the business and technical direction of the company. This position provides the qualified candidate with an opportunity to join our smart, motivated team and to directly impact our business. Core responsibilities include:
- Lead a team of senior data analysts and software developers to deliver industry-best web analytics services.
- Develop novel statistical modeling techniques for pattern recognition problems.
- Assess the quality, viability, and efficiency of analytical models.
- Design rock-solid automation solutions to ensure the integrity, availability, and freshness of analytics products.
- Lead technology discussions and guide the technical direction of data ingestion, storage, and analysis platforms.
- Contribute to strategic planning and project management for a variety of technical initiatives.
- Develop processes for optimizing throughput, documenting methodologies, and increasing our institutional knowledge based on experimental results and operationalized solutions
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