Job Opportunities

Data Science Engineer

Data Science Engineer


We are building enterprise data governance solutions for tomorrow. At the heart of our ambition is to codify the enterprise data model and build auto healing and remediation capabilities based on insights gained from such a model. We call this the Enterprise Knowledge Graph.


The role


We are looking for a Data Science Engineer to join our team to help build our pilot that has gone through various stages of ideation. Entering a project at such an early stage has many advantages – you get to shape the product in your vision and drive the future roadmap. You will interact with our pilot clients to ensure that we are able to continuously learn from their applications and use cases. Most importantly, you get to play an integral role in solving abiding data governance challenges in enterprises today.


We are looking for engineers who have worked on machine learning models, have deployed convolutional neural networks and its variants using TensorFlow/Pytorch for enterprise B2B and B2C user cases. Strong programming skills in Python, together with data engineering experience with large complex datasets are a necessity and so is experience with deploying ML ops with Azure Machine learning, AWS Sagemaker or Google cloud. Experience in integrating large language model frameworks like LangChain for Natural Language Processing (NLP) applications is desirable. A background in Cyber Security and/or Cloud Ops will be like an icing on the cake, but this is not essential.


You will be a self-starter, passionate about problem solving, you will work with the product team and our clients collaboratively to delight them with your inventiveness and attention to detail.



Core Responsibilities:

Model Development: Design and deploy Machine Learning models, specifically focusing on Convolutional Neural Networks (CNNs) and their variants for B2B and B2C use cases.

MLOps & Deployment: Manage the end-to-end ML lifecycle using platforms such as Azure Machine Learning, AWS SageMaker, or Google Cloud.

Data Engineering: Handle large, complex datasets to support model training and enterprise-scale insights.

Collaboration: Work alongside the product team and clients to deliver inventive solutions with high attention to detail.

Technical Qualifications
Programming: Mastery of Python is a necessity.

Frameworks: Deep experience with TensorFlow or PyTorch.

NLP & LLMs: Proficiency in integrating Large Language Model (LLM) frameworks like LangChain for Natural Language Processing applications is highly desirable.

Data Expertise: Proven experience in data engineering with complex enterprise datasets.