Senior Data Scientist
Emmes Global
- Bangalore, Karnataka
- Permanent
- Full-time
- Leverage state-of-the-art deep learning techniques to build scalable and high-performance solutions that drive innovation and efficiency.
- Utilize advanced architectures such as Long Short-Term Memory (LSTM) networks, Large Language Models (LLMs) and transformer-based models (e.g., BERT, GPT, T5) for tasks like text generation, sequence modeling, entity recognition and context-aware recommendations.
- Evaluate problem requirements and data features to select and implement the most suitable AI methodologies, including self-learning, reinforcement learning or other advanced techniques.
- Ensure chosen approach aligns with business objectives while balancing model accuracy, interpretability and computational efficiency.
- Train, fine-tune and evaluate AI/ML models using AWS services such as Amazon SageMaker, Amazon Bedrock and ML Compute to ensure scalability, robustness and cost-effectiveness in cloud-based environments.
- Collaborate with engineering teams to integrate and operationalize AI models into production systems, enabling real-time predictions and data-driven decision-making while ensuring reliability, scalability and low-latency performance.
- Analyze, process and extract actionable insights from complex datasets stored across AWS services such as Amazon S3, Redshift, RDS and DynamoDB.
- Utilize SQL, Python and other relevant programming languages to perform data wrangling, transformation and feature engineering to support AI model development.
- Explore and visualize large-scale datasets to identify patterns, trends, correlations and anomalies that can enhance AI model training and decision-making.
- Leverage statistical analysis, data mining techniques and domain knowledge to improve data-driven insights.
- Collaborate with data engineers and AI engineers to design and optimize scalable data pipelines and infrastructure.
- Ensure seamless data ingestion, processing and integration for AI models, enhancing efficiency, automation and real-time capabilities.
- Communicate the insights and implications of your AI models to stakeholders in a clear and concise manner, bridging the gap between technical expertise and clinicians.
- 4+ years of experience as a Data Scientist or similar role, with a strong focus on AI and machine learning.
- Proven experience in designing and implementing production-grade data-driven AI models.
- In-depth understanding of deep learning, self learning, reinforcement learning or other relevant AI techniques.
- Expertise in Python and familiarity with AI libraries such as TensorFlow, PyTorch, Scikit-Learn, etc.
- Strong understanding of probability theory, statistical analysis and machine learning methods.
- Excellent communication and collaboration skills.