Technology Lead Job in Bengaluru at Broadridge

Broadridge is hiring for the role of Technology Lead!

Responsibilities of the Candidate:

• Perform Exploratory data analysis, form the solution approach, and then design & develop model pipelines, using AWS Sagemaker for model experimentation, training, model promotion, etc. 
• Use machine learning and statistical modeling techniques such as Reinforcement Learning, Decision Trees, Logistic Regression, Bayesian Analysis, Neural Networks, and others to develop and evaluate algorithms to improve product/system performance, quality, and accuracy.  
• Analyse & suggest efficient model retraining strategies, define validation strategy, training models & hyperparameters, verify data quality, model quality, lineage, etc. 
• Stay up to date with state-of-the-art algorithms, repositories, and tools in Generative AI space (LLMs) e.g., Finetuning, quantization, pruning, etc. 
• Mentor and coach junior data scientists and contribute to the continuous learning and development of the data science community. 
• Staying up to the latest AI development, and accordingly suggesting improvements to our roadmap and approaches, and disseminating learnings to colleagues. 
• Help establish standards and best practices around Machine Learning – training and testing framework, coding standards, and engineering practices. 

Requirements:

• Bachelor’s or Master’s, (preferably PhD degree) in Computer Science, Data Science, or a related field with proven experience of 3+ years as a data Scientist working on Advanced Analytics projects in Cloud based environment (preferably AWS) 
• Proficient with Machine learning techniques, statistical/analytical methodologies, and algorithms (e.g. classification, regression, clustering, feature selection/PCA, deep learning, time-series analysis, network analysis, hypothesis testing) 
• Experience with NLP techniques 
• Exhibit proficiency in Python, SQL, and software engineering, along with expertise in deep learning frameworks (ML/distributed ML frameworks like TensorFlow, etc) 
• Familiarity with common ML packages, particularly sci-kit-learn, pandas, numpy, matplotlib, seaborn, XGBoost, etc., or similar. Deep learning experience (e.g. Pytorch or Tensorflow)  
• Cross-functional collaboration with Product Owners, Data Engineers, SMEs, UX designers 
• Understand the model build lifecycle, including feature selection and optimization, model selection and validation, and ongoing model maintenance using ML Frameworks like Sagemaker, MLFlow 
• Exceptional communication skills and ability to present findings to a non-technical audience 
• Experience in effective data visualization approaches and a keen eye for detail in the visual communication of data insights