RESPONSIBILITIES
- Deploying machine learning models - On Prem, Cloud and Kubernetes environments
- Driving data-derived insights across the business domain by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives.
- Creating and implementing data and ML pipelines for model inference, both in real-time and in batches.
- Architecting, designing, and implementing large-scale AI/ML systems in a production environment.
- Monitor the performance of data pipelines and make improvements as necessary
What we’re looking for...
You have strong analytical skills and are eager to work in a collaborative environment with global teams to drive ML applications in business problems, develop end-to-end analytical solutions, and communicate insights and findings to leadership. You work independently and are always willing to learn new technologies. You thrive in a dynamic environment and can interact with various partners and multi-functional teams to implement data science-driven business solutions.
You'll need to have:
- Bachelor's degree with four or more years of relevant work experience.
- Expertise in advanced analytics/ predictive modelling in a consulting role.
- Experience with all phases of end-to-end Analytics project
- Hands-on programming expertise in Python (with libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) , R (for specific data analysis tasks)
- Knowledge of Machine Learning Algorithms - Linear Regression , Logistic Regression ,Decision Trees ,Random Forests ,Support Vector Machines (SVMs) ,Neural Networks (Deep Learning) ,Bayesian Networks
- Data Engineering - Data Cleaning and Preprocessing ,Feature Engineering ,Data Transformation , Data Visualization
- Cloud Platforms - AWS SageMaker ,Azure Machine Learning ,Cloud AI Platform
Even better if you have one or more of the following:
- Advanced degree in Computer Science, Data Science, Machine Learning, or a related field.
- Knowledge on Home domain with key areas like Smart Home, Digital security and wellbeing
- Experience with stream-processing systems: Spark-Streaming, Storm etc.