Data Scientist
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/Gen 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, Sage maker,
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 Data warehousing concepts and ETL processes using Redshift &
SQL Server




• Experienced in using IDEs and Tools like GitHub, AWS Code Commit, Jupyter
Notebooks/Lab and Anaconda.
• Robust 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 visualizations to effectively convey findings using Tableau.

Technical Skills:

- Cloud Platform: AWS
- Generative AI/ Agentic AI
- Big Data: Python, Pytorch, Torch serve, Airflow, TensorFlow
- Databases: Redshift and SQL Server.
- Visualization: Tableau or Quick sight
- Languages: SQL, TensorFlow, Pytorch and Python
- Tools/IDE: Docker, Kubernetes, Airflow, Jupyter Notebooks/Labs and Anaconda
- Operating Systems: UNIX, LINUX
- AWS Services: EC2, Sage maker, RDS, Lambda, Redshift, S3, CloudWatch.
- Packages: MS Office Suite
- DevOps: AWS Code commit
- ML Ops
- Other Tools: Putty

Eng Background
Coding
Commented [SB1]: At least of 2
Commented [SB2]: Must have. Image/ Video analytics/ Deep
learning.
Python package. AWS p.
~ Commented [SB3]: Good to have

📌 Data Scientist (Python, ML, SQL) (Halol)
🏢 QuestW
📍 Halol