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Full Time

Senior Manager – Quantum Computing

Any Location, Remote

Job Description:

Product and Technology (P&T) is focused on standardizing, automating, delivering tools and processes and exploring emerging technologies that drive efficiency and enable our people to reimagine the possible. Process improvement, transformation, effective use of innovative technology and data & analytics, and leveraging alternative delivery solutions are key areas of focus to drive additional value for our firm. If as a professional you are looking to put your skills to work in a product-based, fast paced, entrepreneurial, and inclusive environment, P&T is the team for you. A career in our P&T, will provide you with a unique opportunity to build transformative products and innovative mechanisms that bring new insights to our business and customers that can help identify business gaps, solve problems, and build new business opportunities.

Basic Qualifications:

  • Level: Senior Manager
  • Minimum Year(s) of Experience: 9 – 12 years of overall experience (at least 4+ years in quantum algorithms/quantum cryptography/quantum computing, and rest in AI/Simulation/IOT etc.)
  • Level of Education/ Specific Schools: Graduate/Post Graduate from any college with relevant experience
  • Field of Experience/ Specific Degree: MS/MTech/PhD in Computer Science/Engineering, Physics, Mathematics or related technical field from a reputed institute, or equivalent practical experience.
  • Knowledge Required:
    • Demonstrates intimate abilities and/or a proven record of success in the following areas:
      • At least 4+ years in quantum algorithms/quantum cryptography/quantum computing, and rest in AI/Simulation/IOT etc.
      • Understanding statistical or numerical methods application, data mining or data-driven problem solving
      • Demonstrating thought leader level abilities in the use of statistical modeling, algorithms, data mining and machine learning algorithms
      • 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
      • Leading, training, and working with other data scientists in designing effective analytical approaches taking into consideration performance and scalability to large datasets
      • Manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
    • Demonstrates intimate abilities and/or a proven record of success in the following areas:
      • Demonstrated ability to continuously learn new technologies and quickly evaluate their technical and commercial viability
      • Demonstrating thought leader-level abilities in commonly used data science packages including Spark, Pandas, SciPy, and Numpy
      • Deep understanding of linear algebra, advanced concepts of quantum computing, quantum algorithms
      • Leveraging familiarity with deep learning architectures used for text analysis, computer vision and signal processing
      • Developing end to end deep learning solutions for structured and unstructured data problems
      • Developing and deploying AI solutions as part of a larger automation pipeline 
      • Utilizing programming skills and knowledge on how to write models which can be directly used in production as part of a large scale system
      • Understanding of not only how to develop data science analytic models but how to operationalize these models so they can run in an automated context 
      • Using common cloud computing platforms including AWS and GCP in addition to their respective utilities for managing and manipulating large data sources, model, development, and deployment
      • Experience with research publications on quantum algorithms or applications of quantum computers (e.g., in quantum simulation, linear algebra, cryptography etc.).
  • Experience with following technologies: 
    • Primary skills:
      • Deep understanding of linear algebra, advanced concepts of quantum computing, quantum algorithms, understanding of gate-based quantum systems, IBM Qiskit, D-Wave’s quantum annealing, quantum optimization using D-Wave’s Leap/Ocean, hands on understanding of D-Wave’s QUBOs for solving optimization problems, quantum cryptography, quantum NLP, and good understanding of Python is a must.
    • Secondary skills (good to have):
      • Practical knowledge of applying machine learning & deep learning techniques using Tensorflow, Keras & Scikit-learn packages with Python

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
    • Leading the 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
  • Understanding various aspects of quantum algorithms/quantum cryptography/quantum computing and build new capabilities and solutions
  • Build AI pipelines that ingest, clean data, and make predictions
  • Develop, deploy and manage production pipeline of ML 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
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