Transactional Analytics

2 months ago


Pune Maharashtra, India CRIF Full time

**Key Responsibilities**:

- Analyse large volumes of Credit Data to uncover patterns, anomalies, and trends; and recommend actionable based on analysis.
- Perform Statistical analysis and hypothesis testing.
- Develop and implement analytical models, algorithms, and statistical techniques in alignment to CRIF approach and Standards, to extract insights and drive decision-making.
- Collaborate with internal and external stakeholders to define business objectives and requirements for transaction analytics initiatives.
- Review Model Validation Results and recommend actionable based on outcome.
- Identify opportunities for improvement and optimization of analytical solutions, based on data analysis and performance metrics.
- Stay current with industry trends, best practices, and emerging technologies in transaction analytics and data science.
- Build and maintain dashboards, reports, and data visualizations to communicate findings and insights effectively to various stakeholders.
- Ensure adherence to data governance policies, standards, and procedures.

**Knowledge / Skills**:

- **Statistical Modelling**: Strong knowledge of statistical methods and techniques such as regression analysis, hypothesis testing, clustering, time series analysis, segmentation methodologies (CHAID, CART), Random Forest, Bayesian Methods, and predictive modelling.
- **Programming Languages**: Fluency in at least one programming language commonly used for data analysis and modelling, such as SAS, Python, R, PySpark, or similar.
- **Data Visualization**: Ability to create visually appealing and informative data visualizations using tools like Tableau, etc. and to communicate complex data insights effectively through charts, graphs, and dashboards shall be added advantage.
- **Database Management**: Knowledge of database systems and query languages (e.g., SQL) for retrieving and manipulating transactional data stored in relational databases or data warehouses shall be added advantage.
- **Business Acumen**: Knowledge on Credit and Underwriting, ability to understand business processes, objectives, and stakeholders' requirements to effectively translate business problems into analytical solutions. Strong problem-solving skills and critical thinking abilities to identify opportunities for optimization and improvement.
- **Communication Skills**: Excellent written and verbal communication skills with the ability to convey complex technical concepts and analytical findings to non-technical stakeholders in a clear and understandable manner. Strong interpersonal skills for collaborating with cross-functional teams and presenting insights and recommendations. Proficiency in MS Word, Excel, Access, and Power Point is a must.
- **Continuous Learning**: Commitment to staying updated with the latest trends, advancements, and best practices in data analytics, transaction processing, and related fields.
- **Attention to Detail**: Detail-oriented mindset with a focus on data accuracy, quality, and integrity. Ability to identify discrepancies, outliers, and patterns within transactional data and perform thorough validation and verification procedures.
- **Ability to meet Deadlines**: Commitment to meet deadlines, effective time management and prioritization of tasks, flexibility to adapt to changing product requirements, handle multiple projects under pressure, and effective overall project planning.

**Preferred Qualifications**:

- Education: Bachelor/Masters in Statistics/Mathematics/Economics/Computer Science, or a related field from a leading institution, or equivalent to these degrees.
- 5-7 years’ experience in analytics modelling techniques with especially in Credit Risk and BFSI domain

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