Job
Description
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. Show more Show less
