Data Scientist

As a Data Scientist at NeosAlpha, you will play a crucial role in designing, building, and optimizing machine learning models to deliver impactful data-driven solutions. Your responsibilities will include: - Design, build, and optimize classical ML models such as regression, SVM, decision trees, random forests, clustering, and dimensionality reduction. - Write clean, efficient, and scalable Python code using libraries like NumPy, Pandas, and Scikit-learn. - Implement and fine-tune deep learning models like CNNs, RNNs, and Transformers using frameworks such as TensorFlow or PyTorch. - Work with Generative AI models like LLMs, Transformers, GANs, and VAEs, contribute to prompt engineering, and optimize GenAI models. - Handle large datasets, perform preprocessing, augmentation, and feature engineering for ML workflows. - Deploy models into production, monitor performance, and address issues like drift, bias, or overfitting. - Participate in code reviews, ensure coding best practices, scalability, and maintainability of ML solutions. - Build and automate data pipelines and workflows using tools like Airflow, Spark, or Dataflow. - Collaborate with cross-functional teams to integrate ML/GenAI solutions into real-world applications. Qualifications for this role include: - Bachelors or Masters degree in Computer Science, Data Science, Mathematics, Statistics, or related fields. - Strong expertise in Machine Learning and Python programming. - Good exposure to Generative AI models and fine-tuning techniques. - Experience with ML/DL frameworks such as TensorFlow, PyTorch, or Keras. - Solid mathematical/statistical foundation in probability, optimization, and modeling. - Familiarity with deployment platforms like AWS Sage Maker, Azure ML, GCP AI, and MLOps practices. - Strong coding discipline, with experience in writing optimized, production-ready code. In addition to technical skills, we value the following soft skills and behavioral competencies: - Strong problem-solving and analytical mindset. - Excellent communication and collaboration skills. - Self-motivated, reliable, and detail-oriented. - Ability to manage time effectively and meet deadlines. - Eagerness to learn and adapt to emerging technologies.,