Basic Qualifications:

• Level: Manager
• Minimum Year(s) of Experience: 7- 10 years of overall experience with at least 5 years dedicated advanced analytics and ML
• Level of Education/ Specific Schools: Graduate/Post Graduate from reputed institute(s) with relevant experience
• Field of Experience/ Specific Degree: B.Tech./M.Tech/Masters Degree or its equivalent /MBA
• Preferred Fields of Study: Computer and Information Science, Artificial Intelligence and Robotics, Mathematical Statistics, Statistics, Mathematics, Computer Engineering, Data Processing/Analytics/Science
• Knowledge Required:
  • Experience with a subset in each of the following technologies:
    • Software: AnyLogic, STELLA, Arena
    • Programming: Python, Java
    • Data Processing Tools: Python (Numpy, Pandas, etc.), Spark, cloud-based solutions such as GCP DataFlow;
    • Machine Learning Libraries: Python (scikit-learn, pysim, etc.), TensorFlow, Keras, PyTorch, Spark MLlib;
    • Code collaboration: git, github
  • Independently working on building simulation models using object oriented approaches. Experience with agent based modeling, system dynamics modeling, discrete event modeling
  • Experience with Systems Thinking concepts and application is a big plus.
  • Demonstrated ability to create end-to-end technology prototypes and/or machine learning models for a given business use case or application.
  • Demonstrated experience with rapid prototyping, using agile approaches to quickly test new ideas and “fail fast”.
  • Demonstrated ability to apply a business framing to emerging technology solutions and communicate to business audiences in written and verbal formats.
  • Demonstrated interest in emerging technologies such as Artificial Intelligence, Blockchain, Internet of Things, Virtual Reality, Augmented Reality, and Robotics.
  • Demonstrating proven delivery within a number of large scale projects
  • Demonstrating ownership of architecture solutions and managing change
  • Understanding business development such as client relationship management and leading and contributing to client proposals
  • Communicating project findings orally and visually, to both technical and executive audiences
  • Developing people through effectively supervising, coaching, and mentoring staff
  • Demonstrated contributions in firm development and knowledge building activities such as recruitment, intellectual capital development, staffing, marketing, branding
  • Leading, training, and working with other data scientists in designing effective analytical approaches taking into consideration performance and scalability to large datasets
  • Experience in innovation or lab environments is a plus.
  • Excellent communication skills

Role and Responsibilities:

• Leadership:
  • Leading initiatives aligned with the growth of the team and of the firm
  • Providing strategic thinking, solutions and roadmaps while driving architectural recommendation
  • Interacting and collaborating with other teams to increase synergy and open new avenues of development
  • Supervising and mentoring the resources on projects
  • Managing communication and project delivery among the involved teams
  • Handling team operations activities
• Quickly explore new analytical technologies and evaluate their technical and commercial viability
• Work in sprint cycles to develop proof-of-concepts and prototype models that can be demoed and explained to data scientists, internal stakeholders, and clients
• Quickly test and reject hypotheses around data processing and machine learning model building
• Experiment, fail quickly, and recognize when you need assistance vs. when you conclude that a technology is not suitable for the task
• Build machine learning pipelines that ingest, clean data, and make predictions
• Develop, deploy and manage production pipeline of ML and simulation models; automate the deployment pipeline
• Stay abreast of new AI research from leading labs by reading papers and experimenting with code
• Develop innovative solutions and perspectives on AI that can be published in academic journals/arXiv and shared with clients