We Are Hiring!

Integrant is looking for game changers to join our team as "Data Scientist - AI & Machine Learning" with below roles and responsibilities:

Use mathematics, statistics, machine learning, and artificial intelligence techniques to extract knowledge and insights from structured, semi-structured, and unstructured data.
Design, develop, evaluate, and deploy predictive and prescriptive machine learning models.
Conduct open research and experimentation to develop innovative solutions for complex client challenges.
Engage with clients and stakeholders to understand business needs and translate them into AI and Data Science solutions.
Design and implement end-to-end Machine Learning and Generative AI solutions.
Build and optimize Retrieval-Augmented Generation (RAG) systems and intelligent agent-based applications.
Develop scalable model deployment and monitoring solutions using MLOps best practices.
Monitor model performance, detect concept drift, and continuously improve deployed systems.
Collaborate with software engineering teams to productionize AI applications and ensure reliability, scalability, and maintainability.
Mentor and coach junior Data Scientists and Machine Learning Engineers.
Lead technical discussions, knowledge transfer sessions, and client-facing AI engagements.
Stay current with emerging AI, Machine Learning, MLOps, and Generative AI technologies and frameworks.

Education & Experience

- 7+ years of professional experience, including 5+ years in Data Science, Machine Learning & MLOps
- MSc in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative discipline.
- Experience mentoring, coaching, or leading technical team members.

Data Science & Machine Learning

- Strong foundation in Machine Learning techniques including Classification, Regression, Clustering, Association Rule Mining, Feature Engineering, and Model Evaluation.
- Experience with Deep Learning concepts and frameworks.
- Extensive hands-on experience with Python and the Data Science ecosystem.
- Experience with one or more ML frameworks such as Scikit-Learn, TensorFlow, Keras, or PyTorch.
- Experience conducting research, experimentation, and hypothesis-driven analysis.

MLOps & Production AI

Generative AI & Agentic AI

Cloud & Data Engineering

Nice to Have:

Advanced AI & Data Science

Reinforcement Learning (RL)
Optimization techniques, including single-objective and multi-objective optimization
Stochastic Local Search methods
Knowledge Graphs and Graph Machine Learning.

Leadership & Consulting

Experience leading AI initiatives and technical strategy.
Experience working directly with international clients and stakeholders.
Experience defining AI architecture, standards, and best practices across teams.

Integrant

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