The Data Scientist / Data Engineer will play a critical role in designing and
implementing data architecture and machine learning models to support AI-driven
initiatives for LeadX 360 Pragma. This position requires expertise in data modeling,
ETL processes, and ML development to optimize LeadX 360 Pragma's AI features,
including lead probability ranking, recommendation engines, and NLP tasks. The
candidate will work closely with cross-functional teams to ensure seamless
integration of AI/ML components with data architecture and UI, providing high-
quality, data-driven insights to end users.

Key Responsibilities: 1. Data Architecture and Modelling  Design robust data models and workflows to maximize the effectiveness and scalability of AI/ML solutions.  Collaborate with team members to create a data architecture that supports real-time data processing and model execution. 2. Data Integration and ETL Processes  Implement and maintain ETL (Extract, Transform, Load) processes for efficient data integration and pipeline automation.  Standardize and cleanse data from multiple sources to provide consistent, high-quality data for AI/ML model training and predictions. 3. Data Quality and Integrity  Ensure data accuracy, consistency, and reliability by establishing data quality standards and conducting regular audits.  Develop monitoring systems to promptly identify and resolve any data inconsistencies or issues.

4. Machine Learning Model Development  Develop, train, and deploy machine learning models using frameworks like TensorFlow, Scikit-learn, etc.  Optimize models for key applications, including lead probability scoring, recommendation engines, and NLP, ensuring high accuracy and performance. 5. Model Training and Optimization  Conduct thorough model training, testing, and optimization to ensure robust performance in various scenarios.  Utilize advanced techniques such as hyperparameter tuning and cross- validation to refine model outputs. 6. Integration with Data Architecture and Frontend/UI  Integrate AI/ML models within the existing data architecture and work with frontend/UI teams for seamless functionality.  Collaborate with software engineers to embed AI features within the LeadX 360 Pragma application for an enhanced user experience. 7. Quality Assurance and Testing  Partner with QA Engineers to develop testing protocols, validate model performance, and conduct developer testing.  Identify and troubleshoot issues in the model output and optimize as needed to improve accuracy and efficiency.

Ideal Qualifications:  Education: Bachelor’s or master’s degree in data science, Computer Science, Engineering, or related field.  Experience: 4+ years in data science, data engineering, or related field, with a proven record of developing and deploying machine learning models.  Technical Skills: o Proficiency in data architecture, data modelling, and SQL.

o Experience with ETL tools and data pipeline automation. o Strong programming skills in Python or R, with experience in ML libraries such as TensorFlow and Scikit-learn. o Familiarity with cloud platforms (AWS, GCP, or Azure) is advantageous.

 Soft Skills: o Strong problem-solving skills with a keen attention to detail. o Ability to communicate effectively with cross-functional teams and present complex data insights clearly. o A collaborative mindset, with a commitment to quality and continuous improvement.