Primary Purpose :

Our client is seeking a talented and motivated Data Scientist to join their team and play a key role in developing innovative AI solutions using the AWS technology stack.

You will be responsible for developing, assessing, and fine-tuning various AI and machine learning models and oversee training, testing and deployment of these models.

You will work closely with cross-functional teams, including, data engineers, AI engineers, software engineers, DevOps engineers and product managers, to bring AI-powered solutions to life and drive clinical trial acceleration and insights.

Responsibilities :

ML Model Development and Deployment :

- 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 modelling, 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.

Data Expertise and Infrastructure :

- Analyse, 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.

Collaboration and Communication :

- 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.

- Stay up-to-date on the latest advancements in AI research and translate them into practical applications for the company.

Qualifications :

- 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.