Data Scientist

Job Description

Job Summary We are looking for a Data Scientist to analyze and interpret complex data sets, uncover patterns, and derive actionable insights. The role involves developing data models and algorithms tailored to project requirements, implementing data validation strategies to ensure data quality, and collaborating with AI/ML engineers to integrate models into the conversion engine system. You will also be responsible for presenting findings and strategic recommendations to stakeholders and leadership. A willingness to experiment and learn from failure is essential to thrive in this fast-paced, innovative environment. Roles & Responsibilities Develop AI-Driven Data Conversion Applications: Utilize AI technologies to build intelligent and scalable data conversion tools. Implement AI-Based Data Mapping :Develop AI algorithms to accurately map data from source to target systems. Automate Code Generation :Use AI models to generate transformation code automatically, improving efficiency. Ensure Data Validation :Apply AI-driven validation techniques to maintain data integrity and quality throughout the pipeline. Facilitate Code Conversion :Implement AI solutions for seamless conversion of code between platforms or formats. Collaborate with Stakeholders :Work closely with data engineers, developers, AI solution engineers, and business analysts to integrate the data conversion system. Monitor & Troubleshoot Applications :Continuously monitor the application and resolve issues to ensure optimal performance. Maintain Documentation :Document methodologies, workflows, and development processes for transparency and continuity. Stay Updated with Emerging Technologies :Keep abreast of the latest trends in AI, data science, and data conversion techniques to enhance the solution stack. Must-Have Skills Bachelor’s or Master’s in: Data Science / Computer Science / Artificial Intelligence Or a closely related field 8+ years of Data Scientist build AI-driven data conversion tools Programming Languages [Python; SQL; Java (optional)] AI/ML Frameworks (TensorFlow; PyTorch; Scikit-learn) AI-Driven Applications (Code Generation; Data Mapping; Data Validation; Code Conversion using AI) Databases (SQL Server; MongoDB) ETL / Data Wrangling (ETL Pipelines; Data Wrangling; Master Data Management) Data Science Concepts (Model Building; Feature Engineering; Data Integrity; AI-Augmented Reconciliation) Bonus/Preferred Cloud & Big Data Tools DevOps Tools Certifications / Domain Knowledge Let me know if you have any questions or require further clarification.