Tiger   Analytics is a global leader in AI and analytics, helping Fortune 1000   companies solve their toughest challenges. We offer full-stack AI and   analytics services & solutions to empower businesses to achieve real   outcomes and value at scale. We are on a mission to push the boundaries of   what AI and analytics can do to help enterprises navigate uncertainty and   move forward decisively. Our purpose is to provide certainty to shape a   better tomorrow.

Our team   of 4000+ technologists and consultants are based in the US, Canada, the UK,   India, Singapore, and Australia, working closely with clients across CPG,   Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of   our team leaders rank in the Top 10 and 40 Under 40 lists, exemplifying our dedication   to innovation and excellence.

We are a   Great Place to Work-Certified™ (2022-24), recognized by analyst firms such as   Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among   the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial   Times, Economic Times and Analytics India Magazine.

The growing Financial Services vertical seeks self-motivated   analysts and statistical modelers with superlative technical skills for a challenging role in the Financial Services Modeling & Analytics area.

Responsibilities for this job include working with various   clients to design, develop, and implement models for various retail credit   and fraud scorecards, and risk model development. The role also comes with a   managerial responsibility to set and review tasks, perform QC, and to   supervise, mentor and coach analysts.

As part of larger Financial Services practice, you may get to work on a broad range of business-critical problems across   various work streams. You will be engaging with clients and client partners to understand their business context, and work with a team of data scientists and engineers.

Location:
Chennai/Bangalore/Hyderabad/Remote

Qualification :  • 

Education: Graduate/Master degree in computer science, statistics, econometrics, mathematics, computational finance, or similar • 

Deep knowledge in Quantitative methods / econometrics/ statistics.  

• Strong in Regression analysis, Time series Analysis, optimization.  

• Knowledge of Risk Models and Optimization algorithms.  

• Good working knowledge of SAS, Python and SQL, Machine learning, exploratory data analysis  Responsibilities will include:  

Monitor and validate aggregate model risk in alignment with bank’s risk strategy 

1)You will lead a team of Model validators, who use their predictive and AI Modeling knowledge to review and validate a wide variety of the models  

2) Manage a grwoing Model Validation team responsible for independent first line validation of predictive and generative AI models 

3) Perform independent validations of financial, statistical, and behavioral models commensurate with their criticality ratings

 4) Assist with the validation and review of models regarding their theoretical soundness, testing design, and points of weakness 5) Interpret data to recognize any potential risk exposure 

6) Development of challenger models that help validate existing models and assist with outcome analysis 

7) Ensure compliance with the model risk monitoring framework 

8) Evaluate governance for Model Risk Management by reviewing policies, controls, risk assessments, documentation standards, and validation standards 

9) Exposure to CCAR/CECL/IRB Models are preffered 

10) Evaluate the Bank’s compliance with SR 11-7 regulatory guidance"