Machine Learning Engineer

Crescendo Global Leadership Hiring India; Bengaluru; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Crescendo Global Leadership Hiring India in Bengaluru is seeking a Consultant Data Scientist to build production-grade AI/ML solutions from unstructured and transactional data.

You will apply GenAI, LLM-based techniques, and advanced ML methods (XGBoost, Random Forest, survival analysis) with Python, collaborate with clients, and help scale analytics frameworks.

Qualifications

• 4-7 years of hands-on experience in Data Science, ML, or AI.

Responsibilities

• Build and validate advanced ML and statistical models using structured, unstructured, behavioural, and transactional data.

Skills

Python

Machine Learning

GenAI

Feature Engineering

LLM-based Solutions

Production ML

Git/GitHub

CI/CD

Data Analysis

Communication

Tools

Git

GitHub

CI/CD Tools

Job description

Consultant Data Scientist | 47 Years | Bangalore

Hiring a hands-on Machine learning with strong experience in Machine Learning, Python, GenAI, Feature Engineering, and production-grade model development. This is an excellent opportunity for professionals who enjoy working with raw, unstructured, behavioural, and financial data and building advanced AI/ML solutions from experimentation through production.

Location: Bangalore

Experience: 4-7 Years

Your Future Employer: A leading global AI and Analytics organization offering an opportunity to work on advanced Data Science, Artificial Intelligence, Generative AI, and analytics solutions for global clients.

Responsibilities:

1. Build and validate advanced Machine Learning and statistical models using structured, unstructured, behavioural, and transactional data.
2. Engineer meaningful features from raw data and evaluate their incremental predictive value beyond existing models.
3. Apply LLM-based extraction and GenAI techniques to convert unstructured data into structured, machine-readable signals.
4. Work with advanced modelling techniques including XGBoost, Random Forest, sequence/trajectory modelling, survival/hazard modelling, and Bayesian methods.
5. Take analytical solutions from experimentation to production-grade deliverables, including APIs, libraries, reproducible pipelines, and monitored services.
6. Develop and maintain Python codebases using Git/GitHub, version control, and CI/CD workflows.
7. Collaborate closely with data, engineering, and client teams to develop scalable and reliable AI/ML solutions.
8. Contribute reusable frameworks, methodologies, and learnings to the organization’s AI and Data Science Center of Excellence.

Requirements:

1. 4-7 years of hands-on experience in Data Science, Machine Learning, or AI.
2. Strong proficiency in Python, Machine Learning, Statistics, and Feature Engineering.
3. Hands-on experience with GenAI, LLM-based solutions, or AI/agentic workflows.
4. Strong knowledge of advanced ML techniques such as XGBoost, Random Forest, HDBSCAN, HMMs, sequence modelling, survival analysis, and Bayesian modelling.
5. Experience taking models from experimentation to production, rather than working only with notebooks.
6. Strong experience with Git/GitHub, CI/CD, and production ML workflows.
7. Ability to work with raw, unstructured, behavioural, or transactional datasets.
8. Strong analytical, problem-solving, and communication skills.
9. Experience in financial services, lending, credit bureau, risk analytics, or transaction data will be an advantage.
10. Experience with AI evaluation, observability, model monitoring, drift detection, or hallucination checks will be a plus.

What is in it for you:

1. Opportunity to work on advanced AI, GenAI, Machine Learning, and Data Science use cases.
2. Exposure to complex financial, behavioural, transactional, and unstructured datasets.
3. Opportunity to build and deploy production-grade ML solutions using modern AI/ML practices.
4. Opportunity to collaborate with global clients and contribute to reusable AI and Data Science frameworks.

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