Description

• Serve as expert in Data Science, build framework to develop Production level DS/AI models.  
• Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients. 
• Lead multiple teams across clients ensuring quality and timely outcomes on all projects. 
• Lead and manage the onsite-offshore relation, at the same time adding value to the client. 
• Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions. 
• Build a winning team focused on client success. Help team members build lasting career in data science and create a constant learning/development environment. 
• Present results, insights, and recommendations to senior management with an emphasis on the business impact.  
• Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization. 
• Lead or contribute to org level initiatives to build the Tredence of tomorrow. 

Eligibility Criteria: 

• Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Statistics, Data Science) or equivalent experience.  
• 8-20 years of experience in data science, building hands-on ML models 
• Experience in Retail industry preferred.
• Expertise in ML – Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning. 
• Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines  ANOVA , Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers.
• Knowledge of programming languages SQL, Python/ R, Spark. 
• Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch). 
• Experience with cloud computing services (AWS, GCP or Azure) 
• Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing 
• Knowledge in GPU code optimization, Spark MLlib Optimization.  
• Familiarity to deploy and monitor ML models in production, delivering data products to end-users. 
• Experience with ML CI/CD pipelines. 
• Knowledge and exposure to Gen AI

Key Skills

Education

Bachelor's or Master's degrees