Data Science Intern

Position Description

Enfinite Technologies is looking for data scientists to help us innovate and build cutting edge AI and machine learning-based solutions using the millions of records of structured and unstructured, real-time, time-series based data that we collect from our customers oil and gas wells. We're seeking candidates interested in a 3-month internship with our data science team and, based on the candidate's performance, there will be an option to join us in a full-time capacity at the end of the internship period.

Role Summary

• Understanding the business objective and formulating problem statements.
• Analyzing data to gain critical insights.
• Ability to communicate insights and results to both non-technical and technical audiences.
• Experimenting with different modelling architectures to create an optimal setup for model performance as well as computational performance.
• Working with a team of highly motivated data-scientists to build production ready timeseries-based models for failure forecasting and autonomous process optimization.

Educational Qualifications

Working towards a Bachelors/Masters/PhD in a quantitative discipline (Applied Mathematics, Statistics, Computer Science, Engineering or related fields).

Requirements

• Strong programming skills in Python.
• Strong foundational knowledge of Deep Learning principles (for e.g., experience with deep learning Frameworks such as TensorFlow, Pytorch etc.)
• Experience with projects in multivariate timeseries forecasting and/or timeseries classification.
• Strong practical knowledge of deep learning architectures such as RNN’s, Encoder-Decoders and CNN’s, especially in the context of timeseries data.

Additional Skills (Supplementary to the Requirements)

• Experience with SQL Databases like PostgreSQL, TimescaleDB
• Experience with projects using Reinforcement Learning and/or Transfer Learning principles.
• Exposure to cloud computing services, preferably AWS.
• Experience with containerizing ML applications using Docker.