Data Scientist with Machine Learning/Senior Consultant Specialist

In this role, you will:

1. Design, develop, and deploy machine learning models and algorithms especially in 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 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 tech, prototype with and learn new technologies, proactive in technology communities
8. Develop & maintain ML models for 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

Requirements

To be successful in this role, you should meet the following requirements:

1. Minimum 10 years of software development experience. 5+ years of relevant experience in ML technologies mentioned below.
2. Excellent problem-solving and communication skills.
3. Strong experience in Python (3.x).
4. Excellent working knowledge on scikit-learn, classical ML Model development
5. Good experience of SQL, Oracle/PostgreSQL, any NoSQL database, File buckets.
6. Experience in using data from data lake
7. Excellent knowledge and demonstrable experience in using open-source NLP packages such as NLTK, Word2Vec, SpaCy.
8. Experience in setting up supervised & unsupervised learning models including data cleaning, data analytics, feature creation, model selection & ensemble methods, performance metrics & visualization
9. Solid understanding of ML algorithms, ML statistics, and data structures.
10. Excellent interpersonal, presentation and analytical skills.
11. Familiarity with MLOps practices for model deployment and monitoring.
12. Experience working in banking domain with exposure credit monitoring
13. Experience in automating the continuous integration/continuous delivery pipeline within a DevOps Product/Service team driving a culture of continuous improvement

Location : Pune and Bangalore