- Building end-to-end data pipelines for ML models, other data driven solutions such that the pipeline is directly usable for deployment/implementation.

- Building and maintaining data pipelines, data cleaning, transformation, roll-up, pre processing, etc.

- Building/developing data insight solutions various teams like Credit, Collections Distribution, Vigilance, HR, etc.

- Building automation solutions using Python, SQL, Docker, etc. as required.

Technical Skills :

Must have :

1. Primary skill set :

- High Proficiency in Python coding along with good knowledge of SQL (joins, nested query, etc.)

- Data analysis experience.

- Understand and identify the data points and data acquisition mechanism for structured and unstructured data (text/json/xml) for machine learning data pipeline.

- Knowledge of using Python Libraries such as Pandas, sqlalchemy (or other Python SQL related libraries), [good to have : matplotlib, numpy, scipy, scikit-learn, nltk].

- Working knowledge of GIT repositories (any of the Github, Gitlab etc.)

2. Data management skill sets :

- Ability to understand data models and create the ETL jobs using Python scripts.

- Automate regular data acquisition, application process etc. using Python scripts.

Good to have (must be open to learning if doesnt have already)

3. Web API technology :

- Experience in Rest API developments using any of Django, Flask, Fast API etc. (this will be highly appreciated)

- Deployment of web API on cloud using Docker (this will be highly appreciated).

Other useful skills :

- Working knowledge of Linux. (this will be highly appreciated).

- Should be able to work on problems independently or with less support

- Concept of bigdata and Spark (PySpark) knowledge