Data Scientist

questW; Panchmahal District; On-site; INR 1,200,000 - 2,600,000; Full time

Job summary

questW seeks an experienced ML/DL engineer to build and maintain machine learning systems across problem statements to deployment stages. You will perform thorough EDA, apply statistical methods, and develop prototypes and predictive models using Python, TensorFlow, and PyTorch.

The role requires hands-on AWS cloud services experience (SageMaker, EC2, S3, Redshift) and capability to deploy models via APIs, with strong collaboration and documentation skills in a dynamic team.

Qualifications

• 5+ years of strong experience in building and maintaining machine learning and deep learning systems.
• Experience in detailed exploratory data analysis (EDA) and solid statistical knowledge.
• Hands-on with AWS cloud services and ML deployment pipelines.
• Experience deploying models via APIs and on edge devices with secure methods.
• Knowledge of NoSQL databases (Cassandra, MongoDB) and data warehousing (Redshift, SQL Server).
• Proficiency in Python, Linux shells, and data visualization (Tableau optional).

Responsibilities

• Develop prototypes, proofs of concepts, algorithms and predictive models.
• Analyze structured and unstructured data from problem statement to deployment and business impact.
• Build data pipelines, leverage ML/DL/Gen AI to derive insights for stakeholders.
• Deploy models on AWS (SageMaker) and monitor performance via API endpoints.
• Collaborate in a team, document findings, and adapt to fast-changing environments.

Skills

Python

SQL

TensorFlow

PyTorch

EDA

Statistics

Cloud AWS

Docker

Kubernetes

Data Visualization

Tools

Airflow

Jupyter Notebooks

Anaconda

GitHub

AWS SageMaker

Apache Spark

Kinesis

Redshift

EMR

Job description

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

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.

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:

• Databases: Redshift and SQL Server.
• Languages: SQL, TensorFlow, Pytorch and Python
• Tools/IDE: Docker, Kubernetes, Airflow, Jupyter Notebooks/Labs and Anaconda
• Other Tools: Putty

Eng Background

Coding

• Commented [SB1]: At least of 2
• Commented [SB2]: Must have. Image/ Video analytics/ Deep