VMock

Analytics Manager

Gurugram, HR, IN

26 days ago
Save Job

Summary

About the Company:

VMock is a Career Acceleration Platform which is powered by Artificial Intelligence. Our aim is to empower students and professionals along the various phases of their career journey across the globe. Our fast-paced culture is a great fit for anyone looking to make a mark through their work to create impact globally while working with high caliber team members.

Our Mission:

  • Accelerate every student and professional’s career journey to maximize their success.

Our Vision:

  • Offer SMART Career Acceleration Platform that acts like a personal coach to every job seeker along their career journey, globally.

Our Tenets:

  • Innovate - Innovation is at the heart of all our work at VMock. We deal with science fiction on a daily basis, and our vision is no less than something from Star Trek
  • Collaborate - Our ‘ecosystem’ mindset is focused on providing a seamless experience to our customers.
  • Delight - Each of us, here, is an army of one, contributing to our company’s vision. We are constantly engaged to deliver something ‘extra’ to our clients.


About the Role

Lead the development and implementation of comprehensive product ML strategies, specializing in cutting-edge analytics and AI solutions including machine learning, deep learning, and generative AI applications. Partner with the ML Lead to spearhead algorithm development and foster seamless collaboration across Data Science, Product, and Engineering teams, while ensuring ML solutions effectively address key business stakeholder needs.


Responsibilities:

Product Strategy & Roadmap:

  • Define the vision, strategy, and roadmap for ML-based products.
  • Identify and prioritize business problems that can be solved using machine learning.
  • Stay up to date with industry trends, emerging AI technologies, and competitor offerings.


Technical Responsibilities:

  • Drive end-to-end ML strategy, including algorithm design, model architecture selection, and optimization approaches to meet product goals and performance requirements
  • Establish comprehensive evaluation frameworks covering model performance, fairness metrics, and ethical AI considerations
  • Oversee technical validation of ML methodologies, from feature engineering to model deployment, ensuring alignment with business objectives
  • Develop and maintain model governance standards to ensure compliance with industry guidelines while optimizing business impact


Team Collaboration & Leadership:

  • Work closely with data scientists, engineers and designers to develop ML models and integrate them into products.
  • Partner with product teams to define clear problem statements and success criteria for ML initiatives
  • Mentor, guide data scientists in problem formulation and solution approach
  • Present ML insights and recommendations to stakeholders, using data visualization to communicate complex concepts
  • Develop roadmaps and prioritization frameworks for ML initiatives in collaboration with product and engineering teams


Performance Monitoring & Optimization

  • Define business metrics for evaluating ML model performance. Monitor model performance in production and drive improvements based on feedback and real-world data.
  • Ensure continuous learning and iteration of models to improve accuracy and efficiency.


Requirements:

  • Bachelors in Computer Science, Engineering, Mathematics, Statistics, or Data Science
  • 5+ years experience in developing business cases and long-term roadmaps for analytics products
  • 2+ years experience building and scaling products focused on machine learning/predictive modeling, natural language processing, statistical analysis, simulation modeling
  • Knowledge of data visualization tools and SQL-preferable
  • Technical Knowledge: Good understanding of machine learning concepts, model development lifecycle, and AI technologies.
  • Data-Driven Decision Making: Ability to analyze data, interpret ML model outputs, and drive product decisions based on insights.
  • Stakeholder Management: Experience working with data science, engineering, product and business teams.


Additional Benefits -

  • Best in class Tools of trade
  • Medical Insurance
  • Fast Pace Environment to foster growth

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