Grow with us

Our Exciting Opportunity
Responsible for developing scientific methods, processes, and systems to extract knowledge or insights to drive the future of applied analytics. Provide thought leadership, perform Advanced Statistical Analytics, and create insights into data to provide to the business actionable insights, identify trends, and measure performance to address business problems. Collaborate with business and process owners to understand business issues, and with engineers to implement and deploy scalable solutions, where applicable.

What you will do:
• Ensure data science leadership
• Synthesize problems into data question(s)
• Decide approach for data science
• Design & perform data science experiments
• Develop Data Science Infrastructure & Tools
• Convert data into actionable insights
• Act in external relations

• Ensure a seamless transition of AI models from prototype to production applications

• Enhance the reliability and scalability of AI models in production

To be successful in the role you must have:

Theoretical Knowledge:
• Common and advanced clustering algorithms including probability density and distribution based
• Convolutional Neural networks (CNN)
• Recurrent Neural Networks (RNN)
• Transformers
• Graph Neural Networks (GNN)
• Bayesian based probabilistic graphical models
• Deep Autoencoders
• Latest machine reasoning techniques
• Reinforcement learning
• Generative AI

Application of ML/AI:
• Clean clustering of high dimensional data with noise
• Application of autoencoders to high-dimensional data
• Application of GNN to high dimensional complex data structures
• Application of CNN to high-dimensional temporal data
• Application of RNN to high- time series data for forecasting
• Application of Bayesian dimensional networks for causal reasoning
• Auto learning of network structure from data for probabilistic graphical models

• Application of MLOps principles to productized AI models

Frameworks, Languages, & General skills:
• Strong programming skills in Python, ability to write object oriented and scalable code
• JupyterHub and notebooks
• Strong skills in the use of current state of the art machine learning frameworks such as PyTorch, Tensorflow, Keras, scikit-learn, etc.
• Ability to handle large amounts high dimensional data (knowledge of distributed data pipelines is a plus)
• Good data visualization skills

• Strong collaborative skills to partner effectively with DevOps teams

• Enthusiastic about knowledge sharing and keen to participate in and lead initiatives within a collaborative data science community

• Ability to work independently and be a self-starter with high energy, enthusiasm and persistence