- Location
- Mumbai, Maharashtra, India
- Job type
- Full-time
Required skills
- Python
- AWS
- Artificial Intelligence
- Azure
- data ingestion
- deep learning
- Docker
- end-to-end
- fintech
- forecasting
- GCP
- Git
- Kubernetes
- machine learning
- NLP
- SQL
- statistics
- TensorFlow
- Pytorch
About the role
Website:
neo.group
Job details:
Responsibilities:
- Design, develop, and deploy scalable machine learning models for wealth management use cases such as portfolio optimisation, investment recommendations, client segmentation, risk profiling, and financial forecasting.
- Build and maintain end-to-end ML pipelines, including data ingestion, feature engineering, model training, deployment, monitoring, and retraining.
- Develop AI/LLM-based solutions for financial research, document intelligence, and advisor productivity.
- Collaborate with product, engineering, and investment teams to translate business problems into data-driven solutions.
- Ensure production-grade ML systems with a focus on scalability, explainability, performance, and reliability.
- Evaluate emerging AI/ML techniques and drive innovation across financial products.
Requirements:
- Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, Mathematics, Statistics, Electrical Engineering, or a related quantitative discipline.
- Preferred candidates from premier institutes such as IITs, IISc, ISI, BITS Pilani, IIITs, or globally recognised universities.
- 0-3 years of experience building and deploying production-grade machine learning solutions, preferably in wealth management, financial services, fintech, or other data-intensive domains.
Expertise Required:
- Strong foundation in machine learning, deep learning, probability, statistics, linear algebra, and optimisation.
- Hands-on experience with Python, SQL, PyTorch/TensorFlow, Scikit-learn, and ML frameworks.
- Experience with time-series forecasting, recommendation systems, NLP/LLMs, and MLOps.
- Proficiency with cloud platforms (AWS, Azure, or GCP), Docker, Kubernetes, Git, and CI/CD pipelines.
- Familiarity with financial markets, portfolio analytics, risk modelling, or quantitative finance is highly desirable.
- Excellent problem-solving skills with the ability to build scalable, production-ready AI systems and translate research into business impact.
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