Data Scientist

Machine Learning Engineer

Help design, implement, and validate the ML Pipelines while collaborating with other data scientists.

Coordinate and collaborate with other Software Development group so that ML Pipeline fits well with the rest of our software applications.

Balance adding new features with the need for stability and performance.

Grow development capabilities to align with the pace of business needs.

Master's degree or higher in Computer Science, Computer Engineering, Electrical Engineering or similar discipline with industrial experience in software development.

3+ years of experience with Python coding.

3+ years of recent experience working as a Data Scientist in industry.

Experience with developing production-grade code, preferably in Python.

Experience with data science and machine learning, including Python libraries such as NumPy, SciPy, Pandas and Scikit-learn.

Strong professional written and verbal communication skills.

Ability to pass a Data Science skills-based test.

Experience with relational or NoSQL databases such as Oracle/Cassandra/Redis or similar.

Ability to create model-ready data from raw data, at scale.

Ability to translate business problems into data science pipelines.

Comfort with ML theory to recommend solutions beyond the standard libraries.

Must be able to work independently and as part of a diverse interdisciplinary and international team.

Communicates clearly to technical and non-technical audiences.

Empathy with customer business challenges.

Ability to map business problems to software and data science techniques.

Understanding of fundamental data science and machine learning pipeline including data cleansing, feature engineering, imputation, model tuning, and model prediction.

Basic understanding of the pros and cons of different machine learning algorithms, and basic understanding for different types of open source ML frameworks.

Understanding of hypervisors/containers, especially Docker.