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.
Requirements:
- 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.
Responsibility:
- 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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