Corva is the emerging leader in real-time data and analytics for the oil & gas industry. The world's biggest companies rely on our platform every minute of the day to support their critical operations. We are looking for dynamic individuals to join our Research & Development (R&D) team and contribute to our growing operations and strategic direction. Our team strives to exceed our customers’ expectations with every interaction.

As a data scientist in the R&D department, you will be shaping the technical tools of Corva in data science and machine learning. You will have the opportunity to work with massive amount of data from the fields, as well as data collected from our applications, and will perform full-stack data science work: from data / statistical analyses, to uncovering trends and insights, all the way to building production-ready models that will positively impact the quality of the apps on Corva, and the velocity of innovation across the company. You will be among the first dedicated data scientists in our growing team of data scientists and engineers, and as such, you will have the opportunity to own projects end-to-end and shape the infrastructure and needs of the entire organization in DS and ML. You will report to, and work closely with the ML and stats senior lead, and be included in the R&D team.

Key Roles & Responsibilities

Build and improve machine learning models using Python for our core technologies (drilling and completion)
Develop high quality data science solutions for various business needs
Prototype, productionalize and deploy models using cloud-based tech stacks
Advance the company’s statistical rigor and methodologies, and drive adoption of data products and data science solutions into R&D and other teams’ processes
Help shape the roadmap for DS and ML usage for the company by demonstrating and delivering algorithmic solutions to practical business problems
Do opportunity-sizing for new strategic levers, and help drive direction on the product, operation and marketing teams
Stay current with the latest research and industry trends in ML and related fields, and apply them to solve in-house problems in innovative ways
Be autonomous, eager to learn and motivated by developing the best possible solutions under time constraints (80/20)
Other duties as required

Required Skills & Qualifications

PhD, Master’s degree or equivalent experience in computer science, data science, statistics, or related quantitative fields
Proficiency with Python coding, with good understanding of data structures and practical object-oriented programming experience
Experience with ML frameworks such as sklearn, and deep learning tools such as pytorch or tensorflow
Familiarity with building ML models for image processing and time series analysis
Experience with querying data with noSQL and SQL
Experience with version control systems such as Github
Hands-on experience with prototyping models using Python notebooks and relevant DS/ML packages
Hands-on experience with building ML models for at least classification, regression and clustering problems
Practical experience with using cloud compute solutions such as AWS, GCS or Azure
Experience with ML training, deployment and prediction on cloud-based systems Strong communication, documentation, proactiveness, creativity, and prioritization skills

Recommended Skills & Qualifications

Experience with ML ops tools and platforms
Some knowledge of (or eagerness to learn about) petroleum engineering (drilling, completion, geoscience, production, etc.)
Knowledge of Bayesian statistics and modeling
Knowledge of experimentation (A/B testing)
Experience with distributed data platforms (e.g. MapReduce, Hadoop, Spark)
Experience with building APIs

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