Are you interested in having your products be used by 1000s of brands globally? Does building a global brand excite you? Does having your solutions be used by the world’s top brand get you up from bed? GrowByData is on a mission to expand its distribution to the world’s retailers and is seeking energetic, creative, and self-driven individuals to join the challenge. We are looking for a motivated, and talented individual to join us as Data Science / Machine Learning Engineer. S/he will be responsible to utilize data, machine learning, statistical science, and software skills to craft high -impact solutions that transform our business. If the challenge excites you, please apply with your CV and 3 reasons why this excited you.
REQUIREMENTS
- Proven experience as a Data Science/Machine Learning Engineer
- Understanding of data structures, data modeling and software architecture
- Sound knowledge of math, probability, statistics and ML algorithms
- Ability to write robust code in Python
- Familiarity with machine learning frameworks (like TensorFlow/Keras or PyTorch) and libraries (like scikit-learn)
- Strong communication skills
- Outstanding analytical and problem-solving skills
- Confident, keen to learn new technologies, should have experience on the said technologies
- Self-motivated, eye to detail on tasks
RESPONSIBILITIES
- Work within our data platform and contribute to the development of machine learning systems and data science technical infrastructure
- Study and transform data science prototypes
- Build data pipelines for collecting & processing data from multiple data sources: from the point of ingestion to useful insight
- Select appropriate datasets and data representation methods
- Perform statistical analysis and fine-tuning using test results
- Train and retrain systems when necessary
- Extend existing ML libraries and frameworks
EDUCATION : Bachelor’s degree in Computer Science or Software Engineering
EXPERIENCE
- Prior 2 years of proven experience as a Data Science / Machine Learning Engineer would be preferred and favorable.
