Axio - Decision Scientist

Job Summary :

We are seeking a highly skilled, motivated and curious Decision Scientist to join our Decision Science team. The ideal candidate will have a strong background in machine learning, statistical modeling and computer science, with 2 years of experience in Data Science. Demonstrable experience in building risk, income estimation, fraud estimation, and responder models is a distinct advantage.

Key Responsibilities :

1. Business awareness :

- Understanding of the competitive landscape, axio's product portfolio and data that is available to the team to make credit decisions.

2. Model Development :

Create robust, scalable and explainable predictive models for consumer credit risk mitigation. Own the entire life cycle of the model :

- Identify a specific business challenge and propose an ML solution to it.

- Data collection, cleaning and validation.

- Selection of ML technique, EDA and feature engineering.

- Model training and hyper-parameter tuning.

- Model testing and validation

- Model deployment

- Model monitoring

3. Maintenance :

- Automating and monitoring of various data-pipelines owned by the Decision Sciences team.

- Maintaining various ML models and heuristic algorithms which are in production.

4. Data Analysis :

- Conduct data analysis on large datasets to identify trends, patterns, and insights.

- Use the insights gained from ad-hoc and ML model monitoring analyses to recommend actions to the Decision Sciences team and other cross-functional teams.

- Collaborate with data engineers to gather, clean, and prepare data for modeling and monitoring.

4. Cross-Functional Collaboration :

- Work closely with risk, product, engineering and other business teams to understand requirements and deliver data-driven solutions.

- Communicate complex analytical concepts, results and call to actions to non-technical stakeholders.

Required skills :

- Excellent analytical and problem-solving skills.

- Strong background of concepts from Statistics, Machine Learning and Computer Science.

- Depth of understanding of ML techniques is preferred over breadth.

- Good Python programming skills along with exposure to various Python packages relevant to DS-ML.

- Good understanding of SQL and NO-SQL data storages and retrieval.

- Experience of having processed and analysed large datasets using the Apache Spark ecosystem of tools is preferred.

- Experience of having worked with text analytics, NLP and LLMs is a definite plus.

Following skills are highly desired but not mandatory :

- Exposure to Credit Risk / Income Estimation / Fraud / Responder models in digital consumer lending.

- Exposure to DS-ML practice in a cloud environment like AWS / GCP / Azure.

- Knowledge of Bayesian models and Monte Carlo simulations.

Education : Bachelors/Master's or Ph.D. degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.