Data Scientist/Automation (Python, AcrPy, ArcEQuIS+ etc.)

Responsibilities

• Design and implement scalable data pipelines and ETL processes using Apache Airflow, PySpark, and Databricks.
• Lead development of reusable, version-controlled codebases using Git.
• Apply advanced NLP, OCR, and image processing techniques to extract insights from unstructured data.
• Architect and deploy solutions on Azure, AWS, and GCP using services like Azure Data Factory, S3, Lambda, and BigQuery.
• Build large-scale data processing solutions using Hadoop, Spark, or Databricks.
• Monitor and maintain statistical models and data engineering workflows.
  

• Collaborate with business domain experts to identify opportunities for data-driven solutions.
• Document model designs, algorithm choices, and technical dependencies.
• Participate in cross-functional teams and contribute to strategic initiatives.
• Seek opportunities to add value beyond assigned tasks and mentor junior staff.
  

Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, or a related field.
• 5–8 years of experience in data science, automation, or data engineering.
• Advanced proficiency in Python, Git, and cloud platforms (Azure, AWS, GCP).
• Strong experience with NLP, OCR, machine learning, and image processing.
• Expertise in data pipeline architecture and cloud deployment.
• Excellent problem-solving, communication, and leadership skills.