Data Scientist - Manager (Manufacturing/Sales)

Location

Nagpur | India

Job description

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.

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

Job tags

Salary