Omniful - Data Scientist - Python/Power BI

Role Overview
We are looking for a skilled Data Scientist with expertise in data analytics, machine learning, and AI to join our team.
Data Analysis & Visualization
The ideal candidate will have a strong command of data tools, programming, and knowledge of LLMs and Generative AI, contributing to the growth and automation of our business Responsibilities :

• Develop and manage data pipelines, ensuring data accuracy and integrity.
  

- Design and implement insightful dashboards using Power BI to help stakeholders make data-
driven decisions.

• Extract and analyze complex data sets using SQL to generate actionable Learning & AI Models :
• Build and deploy machine learning models to optimize key business functions like discount management, lead qualification, and process automation.
• Apply Natural Language Processing (NLP) techniques for text extraction, analysis, and classification from customer documents.
• Implement and fine-tune Generative AI models and large language models (LLMs) for various business applications, including prompt engineering for automation & Innovation :
• Use AI to streamline document verification, data extraction, and customer interaction processes.
• Innovate and automate manual processes, creating AI-driven solutions for internal teams and customer-facing systems.
• Stay abreast of the latest advancements in machine learning, NLP, and generative AI, applying them to real-world business :

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• Bachelors or Masters degree in Computer Science, Data Science, Statistics, or related field.
• 4-7 years of experience as a Data Scientist, with proficiency in Python, SQL, Power BI, and Excel.
• Expertise in building machine learning models and utilizing NLP techniques for text processing and automation.
• Experience in working with large language models (LLMs) and generative AI to create efficient and scalable solutions.
• Strong problem-solving skills, with the ability to work independently and in teams.
• Excellent communication skills, with the ability to present complex data in a simple, actionable way to non-technical stakehold
  

(ref:hirist.tech)