Data Scientist
First seen by Alion on Sep 11, 2026.
About the Role :
We are looking for a Data Scientist with strong experience in developing and deploying machine learning solutions for business problems. The ideal candidate should have hands-on expertise across data preparation, statistical and machine learning techniques, model development, experimentation, validation, and productionization, along with exposure to Generative AI and modern AI capabilities.
Key Responsibilities :
- Lead the ML development track within client engagements, from problem definition through deployment.
- Perform data collection, profiling, exploratory data analysis (EDA), feature engineering, and data preparation.
- Develop, experiment with, tune, and validate machine learning and deep learning models.
- Apply appropriate statistical and ML techniques to solve complex business problems across structured and unstructured data.
- Work with supervised, unsupervised, and reinforcement learning approaches where applicable.
- Explore and implement Generative AI and large language model (LLM) use cases, including model adaptation and fine-tuning approaches.
- Evaluate pre-trained models, open-source models, datasets, and third-party AI capabilities for business applications.
- Develop AI/ML solutions across domains such as NLP, computer vision, speech, and structured data, based on project requirements.
- Apply ensemble modelling, model optimization, and responsible AI practices to improve solution quality and reliability.
- Deploy and scale models using appropriate ML deployment and cloud technologies.
- Work with Azure, AWS, or GCP and leverage their AI/ML capabilities for solution development.
- Explore emerging AI technologies and conduct proofs of concept (PoCs) to evaluate their applicability to client and business use cases.
- Propose ML/AI solution approaches, estimate effort, and contribute to solution development and pre-sales activities.
- Present analytical findings, model outcomes, and business recommendations to clients, business users, and project leadership.
- Contribute to AI-based modules and accelerators within organizational solution development initiatives.
- Mentor junior team members and promote adoption of AI/ML best practices across the organization.
- Maintain high standards of model quality, documentation, scalability, security, and responsible AI.
Required Skills :
- 5 - 10 years of experience in Data Science, Machine Learning, or a closely related role.
- Strong hands-on programming experience in Python, R, and SQL.
- Strong understanding of statistical machine learning, deep learning, and model ensembling.
- Experience with data preparation, EDA, feature engineering, experimentation, model tuning, and validation.
- Experience working with supervised and unsupervised learning; exposure to reinforcement learning is an advantage.
- Hands-on experience with Generative AI/LLMs, including model fine-tuning or adaptation approaches.
- Good understanding of NLP, Transformer architectures, embeddings, and modern AI models.
- Exposure to computer vision, speech analytics, or other AI domains is preferred.
- Experience with AI/ML tools for data analysis, model development, deployment, scaling, and fine-tuning.
- Good understanding of open-source and pre-trained models, datasets, and third-party AI platforms.
- Experience with at least one hyperscaler: Azure, AWS, or GCP, with knowledge of their AI/ML capabilities.
- Understanding of Responsible AI, model fairness, transparency, and data privacy.
- Knowledge of model optimization techniques such as quantization and pruning is an advantage.
- Good understanding of software development practices, APIs, and application architecture.
- Strong analytical and problem-solving skills with the ability to break complex problems into structured hypotheses.
- Excellent communication skills with the ability to translate technical AI concepts and findings into business value and actionable recommendations.
- Strong innovation, experimentation, and mentoring capabilities.
Skills
Python, Machine Learning, SQL, Generative AI, NLP, AWS, R, Computer Vision, Data Science, Data Scientist, Artificial Intelligence