Coditas Solutions is seeking a highly skilled and motivated Lead Data Scientist to join our dynamic team. As a Data Scientist, you will play a key role in designing, implementing, and optimizing machine learning models and algorithms to solve complex business challenges. If you have a passion for leveraging AI and ML technologies to drive innovation, this is an exciting opportunity to contribute to groundbreaking projects.

Roles and Responsibilities

• Lead the design, implementation, and optimization of machine learning and AI models using Python and R.
• Develop and deploy scalable predictive models and decision-making systems for business-critical applications.
• Conduct advanced exploratory data analysis (EDA) to extract actionable insights from structured and unstructured data.
• Collaborate with data engineers to ensure high-quality, well-structured datasets for training and inference.
• Own the end-to-end model lifecycle, from development to deployment, monitoring, and continuous improvement.
• Guide the integration of AI/ML models into enterprise-level production systems in collaboration with software engineering teams.
• Provide technical leadership, mentoring junior data scientists and driving best practices in ML model development and deployment.
• Stay ahead of the curve by evaluating and implementing cutting-edge AI/ML advancements, including LLMs and GenAI models.
• Work closely with stakeholders, product teams, and clients to define business challenges and design AI-driven solutions.
• Drive model interpretability, explainability, and responsible AI practices within the organization.

Technical Skills

• 6-14 years of hands-on experience in designing and implementing machine learning, deep learning, and AI solutions.
• Strong programming expertise in Python and R, with proficiency in implementing complex algorithms.
• Extensive experience with cloud platforms (AWS, Azure, GCP) for deploying scalable machine learning solutions.
• Proficiency in MLOps practices, ensuring robust model deployment, monitoring, and retraining workflows.
• Strong background in classical ML algorithms (e.g., linear regression, logistic regression, decision trees, random forests, SVM) and deep learning architectures (CNNs, RNNs, Transformers).
• Hands-on experience with ML/DL libraries such as Scikit-learn, TensorFlow, PyTorch, Keras, NLTK, OpenCV.
• Expertise in data preprocessing, feature engineering, and model evaluation for structured and unstructured data.
• Proven experience in selecting and engineering relevant features to enhance model performance.
• Understanding of LLMs (Large Language Models) and GenAI technologies, with the ability to optimize their usage for enterprise applications.
• Strong problem-solving, critical thinking, and analytical skills to drive AI/ML innovations.
• Exceptional communication and leadership skills, with experience in mentoring teams and collaborating with cross-functional stakeholders.

Join our team and be part of a fast-paced and innovative work environment where your expertise will make a significant impact on our organization's growth and success.