Resy Hiring Drive 2024 For Analyst-Data Science | Location Gurugram

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Resy Hiring Drive 2024: Resy Hiring Drive 2024 for its Analyst-Data Science. Resy Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a Master s degree in the quantitative field or an MBA with analytics experience. if you are interested, please apply as soon as possible.

Company Name: Resy

Role: Analyst-Data Science

Location: Gurugram

Experience: 1 – 3 years

Qualification: Master’s degree in quantitative field or MBA with analytics experience

Batch: Any

Job Type: Full Time

Salary: Best in Industry

Resy Hiring Drive 2024

Job Description:

  • Conduct independent oversight of enterprise-wide models with a focus on a variety of statistical and mathematical models developed and used in Finance, Treasury, Anti-Money Laundering, Climate Risk and Membership Rewards.
  • Conduct gap assessments and establish robust framework to strengthen model risk controls and meet heightened regulatory standards.
  • Conduct research to explore opportunities to elevate model excellence and drive business impact.
  • Communicating results to partners, senior leadership, and various model committees.


  • Hands-on model development or validation experience.
  • Strong Analytical and Relationship and project management skills for driving validation initiatives.
  • Experience in applying advanced statistical and/or quantitative techniques to solve business problems is preferred.
  • Good Verbal, Written, Interpersonal skills and ability to work effectively in a team environment.
  • Willingness to Collaborate with Cross-Functional teams to drive validation and Project Execution.
  • Effectively communicating complex Analytical results to Business Partners and Senior Management.
  • Flexibility and Adaptability to Work Within tight deadlines and changing priorities.
  • Experience with at least one of the data manipulation tools such as Python, Py Spark etc. is a must have.
  • Data Science/Traditional Modeling, Machine Learning/ Artificial Intelligence.
  • Expertise in Coding
  • Supervised and Unsupervised Techniques – active learning, transfer learning, neural models, decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, map reduce techniques, Random Forest, Gradient Boosting, Deep Learning, Text Mining Algorithms
  • Understanding of finance and valuation concepts.


  • Business Outcomes:Effectively challenge the conceptual soundness, theory and approach, purpose/usages of predictive models
  • Maximize business returns by institutionalizing efficient and accurate models.
  • Innovate modeling techniques and variable creation
  • Ensure modeling accuracy and enhance modeling efficiency in existing processes
  • Leadership Outcomes:Put enterprise thinking first, connect the role s agenda to enterprise priorities and balance the needs of customers, partners, colleagues shareholders.
  • Lead with an external perspective, challenge status quo and bring continuous innovation to the existing models
  • Demonstrate learning agility, make decisions quickly and with the highest level of integrity
  • Lead with a digital mindset and deliver the world s best customer experiences every day

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