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Diversity Candidates Only, Full Time

Machine Learning – Manager (Diversity Candidates)

Any Location - Remote

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:
      • Demonstrates intimate abilities and/or a proven record of success in the following areas:
        • Understanding statistical or numerical methods application, data mining or data-driven problem solving
        • Demonstrating thought leader level abilities in the use of statistical modelling, 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
        • 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
        • 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
        • 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 conducting research in a lab and publishing work is a plus
  • Experience with following technologies: 
  • Programming: Python (must) , having experience in R is a plus
  • Machine Learning Libraries: Python (Numpy, Pandas, scikit-learn, gensim, etc.), TensorFlow, Keras, PyTorch, Spark MLlib, NLTK, spaCy)
  • Visualization: Python (like Matplotlib, Seaborn, bokeh, etc.), third party libraries (like Power BI, Tableau) 
  • Productionization and containerization technologies (Good to have): GitHub, Flask, Docker, Kubernetes, Azure DevOps, GCP, Azure, AWS.


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 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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Value Vision Management Consultants
639, 18th Main, 22nd A Cross Banashankari 2nd Stage
Bangalore — 560070


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