Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, and statistical modeling. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. 

Key Roles and Responsibilities of Position:

• Analyze source data and data flows, working with structured and unstructured data (text, audio, images, video, etc.)
• Manipulate high-volume, high-dimensionality data from varying sources to expose and highlight patterns, anomalies, relationships, and trends.
• Apply AI and Machine Learning technology to solve complex, real-world problems.
• Analyze and visualize diverse sources of data, interpret results in a business context and report results clearly and concisely.
• Fulfill problem formulation and ML technique consulting requests in a timely manner.
• Communicate and present analytical models to business customers and executive management.
• Work collaboratively with different business partners and be able to present results in a clear and concise manner.

• Master’s or Ph.D. degree in Computer Science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline preferred. 
• Should have experience in feature engineering, hyper parameter tuning, model evaluation, etc.
• Good exposure to machine learning/text mining tools and techniques such as Clustering/classification like SVM, Deep Learning networks like FRCNN, MRCNN, ResNet, FVRCNN, SalsaNext, NASnet, LSTM Reinforcement learning, and other numerical algorithms.
• Should have experience in using Pandas/Numpy/ScikitLearn, Pytorch, Tensorflow, Keras, ROS, Gazebo, OpenJAUS.
• Practical knowledge of automotive sensors like Camera, RADAR, etc.
• At least 1 year of experience in leading teams of 3-5 data scientists.