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.
(ref:hirist.tech)
