Data Scientist with Machine Learning/Senior Consultant Specialist

HSBC; Bengaluru, Pune City; On-site; INR 12,00,000 - 18,00,000; Full time

Job summary

A leading financial services organization in Bengaluru seeks a Senior Consultant Specialist to design and deploy machine learning models. Responsibilities include analyzing large datasets, optimizing data pipelines, and collaborating with teams to integrate ML solutions. Ideal candidates have a strong background in machine learning and data analysis, and stay updated on new technologies. Join us to help shape the future of banking.

Qualifications

• Experience designing, developing, and deploying machine learning models.
• Proficient in preprocessing and analyzing large datasets.
• Ability to build and optimize data pipelines.

Responsibilities

• Design and deploy machine learning models.
• Preprocess and analyze large datasets for insights.
• Collaborate with ML engineers to integrate solutions.

Skills

Machine Learning

Data Analysis

Algorithm Development

Data Pipeline Optimization

Tools

Oracle

Elasticsearch

Job description

Some careers shine brighter than others.

If you’re looking for a career that will help you stand out, join HSBC and fulfill your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support, and rewards that will take you further.

HSBC is one of the largest banking and financial services organizations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and ultimately helping people fulfill their hopes and realize their ambitions.

We are currently seeking an experienced professional to join our team as a Senior Consultant Specialist.

In this role, you will:

1. Design, develop, and deploy machine learning models and algorithms, especially classical algorithms, to solve business problems.
2. Preprocess and analyze large datasets to extract meaningful insights.
3. Build and optimize data pipelines (extract data from sources like Oracle, Elasticsearch, storage buckets, etc.) for training and deploying ML models.
4. Collaborate with ML engineers and stakeholders to integrate ML solutions into production systems.
5. Research and implement state-of-the-art machine learning techniques and tools.
6. Document processes, experiments, and results for reproducibility and knowledge sharing.
7. Stay up to date with technology, prototype with, and learn new technologies; be proactive in technology communities.
8. Develop and maintain ML models for the credit monitoring domain, e.g., perpetual credit monitoring.
9. Develop innovative solutions in areas such as machine learning, Natural Language Processing (NLP), advanced and semantic information search, extraction, induction, classification, and exploration.
10. Create products that provide a great user experience along with high performance, security, quality, and stability.