Technical Lead, Data Science- AI/ML and Gen AI Technologies

Dear Candidate,

We are hiring!!

Company: Pennant Technologies Pvt Ltd

Domain: Fintech (Banking / Lending, LOS, LMS, Collections)

Role: Technical Lead, Data Science

Location: Hyderabad

Work mode: Work from office (Monday to Friday)

Work experience: 6+ years of work experience in AI/ML and Gen AI Technologies

Interested candidates whose profile is suitable with the mentioned requirement can share your profile to sainikhil.g@pennanttech.com

Job Summary:

The Technical Lead will be responsible for the design, development, and implementation of AI/ML and Generative AI technologies within our platform. This role requires a deep understanding of AI/ML, practical experience in developing and deploying models, and strong technical leadership skills.

Key Responsibilities:

Technical Leadership:

• Lead the development and implementation of AI/ML models and GenAI technologies.
• Mentor and guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
• Collaborate with cross-functional teams to integrate AI/ML and GenAI capabilities into our platforms.

Model Development:

• Design, develop, and deploy machine learning models to solve complex business problems.
• Ensure the scalability, reliability, and performance of AI/ML solutions.
• Conduct thorough testing and validation of models to ensure accuracy and robustness.
• Develop and maintain data pipelines for model training, validation, and deployment.
• Implement and optimize machine learning algorithms for various business applications.

Technical Expertise:

• Stay updated with the latest advancements in AI/ML and GenAI technologies.
• Evaluate new tools and frameworks to enhance the development process.
• Implement best practices for model development, deployment, and monitoring.
• Develop and deploy natural language processing (NLP) models for text analysis and understanding.
• Implement computer vision models for image and video analysis.
• Use reinforcement learning techniques for optimization problems.

Project Execution:

• Manage and execute multiple AI/ML projects, ensuring they are delivered on time and meet the required specifications.
• Develop and maintain project documentation, including design specifications, progress reports, and technical documentation.
• Collaborate with data engineers to ensure data quality and availability for model training and evaluation.

Collaboration and Communication:

• Work closely with product management, engineering, and business development teams to understand requirements and provide AI/ML solutions.
• Communicate complex technical concepts to non-technical stakeholders effectively.

Qualification & Experience:

• Bachelors or masters degree in computer science, Data Science, Engineering, or a related field.
• 6+ years of experience in AI/ML and Gen AI technologies.

Required Skills:

• Strong expertise in machine learning algorithms, data analysis, natural language processing, and generative AI technologies.
• Hands-on experience with AI/ML frameworks and tools such as TensorFlow, PyTorch, scikit-learn, Keras, and others.
• Proficient in programming languages such as Python, R, and SQL.
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• Familiarity with MLOps practices and tools for model deployment, monitoring, and maintenance.
• Knowledge of cloud computing platforms and services (e.g., AWS, Azure, Google Cloud) for AI/ML workloads.
• Understanding of ethical AI principles and data privacy regulations.
• Experience with big data technologies (e.g., Hadoop, Spark) and data visualization tools (e.g., Tableau, Power BI).
• Proficient in using version control systems like Git for collaborative development.
• Knowledge of deep learning techniques and frameworks for neural networks.

Preferred Skills:

• Experience with Low-Code/No-Code platforms.
• Knowledge of banking regulations and compliance requirements.
• Experience with big data technologies (e.g., Hadoop, Spark) and data visualization tools (e.g., Tableau, Power BI).