AVP - Data Scientist.

Job description

**Roles and Responsibilities:** • 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. • Database management and automation. • Working experience on Linux server to installation and configuration of software (related to data science and AI domain), service creation, basic shell scripting etc. • Rest API development and development/management using Docker and related cloud technologies. **Technical Skills** **Must have** • 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.) • Experience in **Rest API** developments using any of Django, Flask, FastAPI etc. (this will be highly appreciated) and Deployment of API on cloud using Docker (this will be highly appreciated). • Hands on experience on **Linux** OS/platform to install software, Python packages, create services, docker creation, automate and run the code/script. •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)** • Other useful skills • Should be able to work on problems independently or with less support • Concept of bigdata and Spark (PySpark) knowledge • Cloud experience (AWS/Azure/GCP)