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

1)Ability to design, execute and interpret statistical analyses to drive insights and strategy related different types of fraud

2)Conducting Independent analysis regarding different types of fraud including but not limiting to first party fraud.

3) Develop and maintain relevant Machine learning models /classical models to mitigate fraud risk

4) Develop strategy to mitigate fraud risk using model output for various product like credit card/debit card, application fraud , ACH etc

5)Work with Product Risk managers and other stakeholders to support new strategy and product development and monitoring

6)Write summary documentation of analyses performed for both technical and non-technical audiences within the firm

7) Present results to peers and higher levels of management

8) Share advanced machine learning and execution knowledge with team members as new techniques are discovered to solve analytical problems

· Experience - must meet one of the following requirements:

· Bachelor's/ Master’s Degree in a quantitative discipline with relevant work experience in analytics

· Bachelor's Degree in a quantitative disciple ( Working knowledge and development experience with SQL, SAS and related tools such as Alteryx and Tableau

· Strong analytical skills with the ability to extract business insights from complex data structures

· Experience coding in a flexible analytics language preferred (e.g. Python, R)

· Proven ability to work with large-scale/complex issues and collaborate across organizations

· Experience in Banking / Digital Banking preferred Prior experience in financial / banking institutions with fraud risk knowledge is a plus