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.
• Valuable 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.
• 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 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 (Halol)
🏢 QuestW
📍 Halol