Data Scientist

Job Responsibilities:

1. Experience in OIL and GAS, Finance
2. Day to Day Operations
3. Deliver high-quality AI models across a broad spectrum of numeric and text analytics
4. Understand the practical scope of the AI models within the products
5. Use modeling techniques which include data acquisition from diverse sources, data exploration, feature engineering, evaluating algorithms/architectures and deploying the models iteratively to improve the final solution.
6. Identify valuable data sources and automate collection processes
7. Undertake preprocessing of structured and unstructured data
8. Build and finetune models
9. Propose solutions and strategies to business challenges
10. Collaborate with Engineering and DevOps teams for deployment
11. Contribute to the team's research activities
12. Build & maintain pipelines
13. Develop and integrate algorithms/packages into the platform
14. Add new ML models to the SAAL platform marketplace
15. Develop customer-centric AI/GenAI solutions
16. Work closely with Product, Support, and Success teams to understand customer needs and contribute to the successful roll-out of the tools into trials and general availability
17. Utilizes state-of-the-art, best-in-class tools, techniques and methods to deliver technical presentations to peers, leadership team, sales executives, clients, prospects, etc.
18. Works collaboratively with various internal stakeholders to bring in synergies to the solution architecture, implementation plan, optimized delivery model and costing.
19. Perform other related duties or assignments as directed.

Minimum Qualifications:

1. Bachelor's Degree in Artificial Intelligence, Business Analytics, Data Science, Computer Science, Mathematics, Engineering or related field
2. Certifications in any technology streams are preferred
3. Minimum 4-6 years or more experience in similar field

Job-Specific Skills:

1. Demonstrable experience in theory and applied areas of Machine Learning/Deep Learning
2. Experience in developing pipelines for both structured and unstructured data
3. Working knowledge in applied NLP (Offline LLM utilization is a plus)
4. Practice with Deep Learning libraries e.g., Tensorflow, PyTorch
5. Seasoned programming skills in Python, Java, R
6. Good experience in RESTifying APIs and Dockerization
7. Extensive Practice in writing good code using suitable data structures
8. Excellent communication skills
9. Broad experience working with Educational/Finance data sets are encouraged
10. Self-motivation and the appetite to build novel solutions or algorithms

Language: French is a plus