Data Scientist: Advanced Statistics/ Analytics/ Machine Learning

/in /by

We are looking for a senior machine-learning expert who will work closely with a cross-functional team of engineers, physicists, and data scientists to identify areas where machine learning can make a difference, to conceptualize and develop datasets using cutting edge, high throughput platforms, and to analyze these data sets using the best machine learning methods, applied at scale. You will need to come up with novel methods that use a broad spectrum of machine learning approaches, including techniques at the forefront of the field. We aim to develop large data sets, and apply cutting edge machine learning methods; hence, you will need to develop and deploy machine learning methods at scale. You will work as part of a team to rigorously analyze our clients’ data, pull out key insights, and make accurate predictions that will let us quickly develop models that have high efficacy and low  false-alarm rate.  You will work closely with a very talented team, learn a broad range of skills, and help shape Sensoleak’s culture, strategic direction, and outcomes.

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Requirements:

  • MS, or Ph.D. in computer science, statistics, mathematics, physics, engineering, or equivalent practical experience.

  • Expertise in one or more general-purpose programming languages (such as Python, C/C++).

  • Demonstrated ability to write high-quality, production-ready code (readable, well-tested, with well-designed APIs).

  • 5+ years of real-world work experience in software development for high-end machine learning algorithms.

  • Significant experience with at least one high-end ML development environment.

  • Demonstrated ability to develop novel machine learning methods that go beyond putting together of existing code, and to apply problem-solving skills to complex issues.

  • Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions.

  • Deep understanding of statistical concepts, multivariate methods, regression, classification, neutral networks, Bayesian logic, time series.

  • Advanced knowledge of a scripting language (Python preferred); experience working with Python Machine Learning packages.

  • Streaming data, SCADA data experience is a plus.

  • Ability to work independently and in collaboration with members of other groups, including data scientists, engineers, software developers, and clients.

  • Experience with O&G data.

  • Experience with scalable machine learning, including the application to large datasets (100TB+).

  • Proficiency in Linux environment (including shell scripting), experience with database languages (e.g., SQL, No-SQL) and experience with version control practices and tools.

  • Familiarity with cloud computing services (AWS or GCP).