05/01 HR
Associate Director - HR at VMock

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VMock - Product Manager - Data Analytics (2-10 yrs)

Gurgaon/Gurugram Job Code: 878978

Objective/Position Summary:

Develop overarching product analytics strategy and execution plan with a focus on advanced analytics, machine learning and AI. Operationalize knowledge graphs and lead every stage of the process from: concept, validation, model building, evaluation and improvement, defining APIs and services, to release within our products--coordinating execution among data science, platform, content and product teams.

Responsibilities:

- Understand business objectives, challenges, competitive trends to create a perspective on the key problems that analytics products should address and translate the same into business outcomes / objectives into technical metrics that drive analytics development efforts

- Manage end-to-end lifecycle for a range of analytics products from ideation through deployment and ongoing product operations

- Use quantitative and qualitative data to make product and research roadmap decisions.

- Work with engineers to build & deploy natural language generation, semantic search, contextual similarity models, natural language parsing models, predictive recommendations along with collaborating with affiliate ML teams

- Stay up-to-date on machine learning and data science trends and best practices

- Understand and translate business and functional needs into machine learning problem statements

- Translate complex machine learning problem statements into specific deliverables and requirements by devising and optimizing product feedback algorithms including scoring thresholds while ascertaining synergies with existing parser capabilities

- Define model evaluation, prioritization, selection strategy for the team and collaborate with development teams to test and deploy machine learning models

- Create metrics to continuously evaluate the performance of machine learning models by proactively determining and computing ML models- accuracy and undertaking pattern analysis

- Maintain and improve the performance of existing machine learning solutions

- Ensure adherence to performance standards and compliance to data security requirements

- Keep abreast with new tools, algorithms, and techniques in machine learning and works to implement them in the organization

- Interpret problems, synthesize analysis, and present information in a way that is understandable to a non-technical person taking advantage of data visualization

- Manage end-to-end lifecycle for a range of analytics products from ideation through deployment and ongoing product operations

- Manage the ML group's roadmap and milestones, setting requirements and driving the development schedule, owning cross-team project statuses and communicating results to a broad audience, brainstorming new project ideas, initiating technical deep dives and engaging in problem solving, and organizing working sessions proactively to identify and mitigate roadblocks.

- Assess risks, anticipate bottlenecks, provide management of critical issues, make trade-offs and balance the business needs versus technical constraints to achieve business goals

Requirements:

- BS in Computer Science, Engineering, Mathematics, Statistics, or Data Science

- Masters in Business Administration (MBA)

- 2+ years- experience developing business cases and long-term roadmaps for analytics products preferably in tech or ed-tech sector or with consulting organizations/KPOs

-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

- Experience with deploying analytics products or solutions to production, and managing ongoing operations of said products or solutions delivering quantifiable business value

- Ability to convert the developed Machine Learning solutions into sustainable offerings

- Strong grasp of principles and approaches used in Data-driven systems, processes and algorithms

Women-friendly workplace:

Maternity and Paternity Benefits

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