Data Scientist - Auto/Infra

Job Requirements:

- 5+ years of strong experience in building & maintaining machine & deep learning models

- Experience in performing detailed exploratory data analysis (EDA) & having sound statistical knowledge

- Understanding of concepts related to algorithm and deep learning architectures

- Develop prototypes, proof of concepts, algorithms, predictive models, and custom analysis

- Analysis of structured and unstructured data from problem statement to model deployment & business impact using ML/DL/AI

- Should be hands on AWS cloud services that includes VPC, EC2, S3, RDS, Redshift, Data Pipeline, EMR, DynamoDB, DevOps, Lambda, Kinesis, DMS, SNS, SQS, Sagemaker, Apache Airflow, and EKS.

- Proficient in big data ingestion and streaming tools like Amazon Kinesis, Beam or Kafka.

- Experience in deploying models via APIs and on the edge devices in a secure manner.

- Good Knowledge/Understanding of NoSQL data bases and hands on work experience in writing applications on NoSQL databases like Cassandra and MongoDB

- Good knowledge on various scripting languages like Linux/Unix shell scripting and Python

- Good knowledge of Datawarehousing concepts and ETL processes using Redshift & SQL Server

- Experienced in using IDEs and Tools like GitHub, AWS CodeCommit, Jupyter Notebooks/Lab and Anaconda.

- Strong team player, ability to work independently and in a team as well, ability to adapt to a rapidly changing environment, commitment towards learning, & documentation skills

- Sound practical knowledge of statistical packages like - R & Python

- Creating data visualisations to effectively convey findings using Tableau.

Technical Skills:

- Cloud Platform: AWS

- Big Data: Python, Pytorch, Torchserve, Airflow, TensorFlow

- Databases: Redshift and SQL Server.

- Visualization: Tableau or Quicksight

- Languages: SQL, TensorFlow, Pytorch and Python

- Tools/IDE: Docker, Kubernetes, Airflow, Jupyter Notebooks/Labs and Anaconda

- Operating Systems: UNIX, LINUX

- AWS Services: EC2, Sagemaker, RDS, Lambda, Redshift, S3, CloudWatch.

- Packages: MS Office Suite

- DevOps: AWS Code commit

- ML Ops

- Other Tools: Putty