Coditas Solutions is seeking a highly skilled and motivated 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 :

- Design, implement, and optimize machine learning algorithms using R and Python.

- Work on developing predictive models and decision-making systems.

- Conduct exploratory data analysis to understand data patterns and insights.

- Collaborate with data engineers to ensure the availability and quality of data for model training.

- Deploy machine learning models into production environments.

- Collaborate with cross-functional teams to integrate models into existing systems.

- Continuously optimize and improve the performance of machine learning models.

- Stay updated on the latest advancements in ML algorithms and technologies.

- Work closely with software engineers to ensure seamless integration of AI/ML solutions.

- Collaborate with clients to understand their business requirements and customize solutions accordingly.

Technical Skills :

- Excellent programming skills with the ability to implement complex algorithms in Python or R.

- Experience with cloud-based platforms (AWS, Azure, GCP) for deploying machine learning models.

- Strong experience of minimum 5 years in developing and implementing machine learning algorithms.

- Experience with model deployment and integration into production systems.

- Hands-on experience with use of standard classical machine learning libraries such as Scikit learn, NLTK, OpenCV as well as deep learning libraries Tensorflow, PyTorch, Keras.

- Understanding of machine learning algorithms, techniques, and concepts (linear regression, logistic regression, decision trees, random forests, neural networks, etc.

- Experience with data preprocessing, feature engineering, and model evaluation techniques of structured and unstructured data.

- Proven experience with identifying, creating and selecting relevant features or variables to enhance model performance.

- Ability to collaborate effectively with cross-functional teams.

- Previous experience working on real-world AI/ML projects.

- Should be focused on linear algebra, machine learning, and statistics & probability are preferred.

- Ability to have a basic knowledge of the LLMs and optimal use of the GenAI models.

- Strong problem-solving and critical-thinking skills.

- Excellent communication and collaboration skills.