3 Jupyter Notebooks Jobs

Position Purpose The main mission of this position will be to leverage data analytics and machine learning techniques to enhance financial decision-making, optimise processes, and mitigate risks . This involves analysing large datasets to uncover insights, developing predictive models to forecast financial trends, and creating data-driven strategies to improve efficiency and profitability. This also includes a capacity to proactively propose axes of improvement of F&S processes through data-driven solutions. Responsibilities Analysing large datasets to identify trends, patterns, and insights that can inform business decisions Designing and developing Predictive (Machine Learning) models Finding, managing and using the most appropriate data sources for modelling purposes Working with expert colleagues and business representatives to examine the results and keep models grounded in reality Documenting each step of the development and informing decision makers by presenting them options and results Ensuring correct implementation of the tools (together with the IT department - FRS) Continuously assessing models by means of back-testing Timely tracking of the deliverables against agreed timeline and budget Arrange smooth go-live implementation and provide post go-live support Present project status regularly to senior management Build and maintain a trusted relationship with all F&S stakeholders across different functions (PMO, IT, finance users, operation teams) Technical & Behavioral Competencies At least 5 years of experience in Machine learning algorithms, Frameworks and industrialisation: Master Degree or higher in Mathematics, Physics, Statistics, Computer science, Data Science or similar background where analytics and figures prevail Degree in Accounting / Finance is a plus Proficiency in programming languages such as Python and R Proficiency in data science tools and environments, such as Jupyter Notebooks and Git Good knowledge of SQL Knowledge of Data Visualisation solution(s) Strong understanding of statistical methods and concepts Having at least sound knowledge of Finance processes and/or systems is a plus Experience of working in Global work environment across cultures appreciated Experience with database management systems Experience with machine learning algorithms and frameworks (professional/academic) Experience in machine-learning models industrialisation Strong listening skills, strong interpersonal skills and a strong cross-functional cooperation between teams Rigorous and dynamic, you like human contact, work as a team and have an excellent organization ability Knowledge of Banking and Financial services Good communication (oral and written), organisation and documentation skills Ability to adapt to change and proficient in problem solving. Capability to work and interact with various people of different expertise and level. Client oriented Collaborative worker & team player Skills Referential Behavioural Skills : (Please select up to 4 skills) Communication skills - oral & written Ability to synthetize / simplify Creativity & Innovation / Problem solving Ability to deliver / Results driven Transversal Skills: (Please select up to 5 skills) Ability to set up relevant performance indicators Analytical Ability Ability to develop and adapt a process Ability to develop and leverage networks Ability to manage / facilitate a meeting, seminar, committee, training Education Level: Bachelor Degree or equivalent Other/Specific Qualifications (if required) Language: Fluent English, French is a plus

Strong in Python and experience with Jupyter notebooks, Python packages like polars, pandas, numpy, scikit-learn, matplotlib, etc. Must have: Experience with machine learning lifecycle, including data preparation, training, evaluation, and deployment Must have: Hands-on experience with GCP services for ML & data science Must have: Experience with Vector Search and Hybrid Search techniques Must have: Experience with embeddings generation using models like BERT, Sentence Transformers, or custom models Must have: Experience in embedding indexing and retrieval (e.g., Elastic, FAISS, ScaNN, Annoy) Must have: Experience with LLMs and use cases like RAG (Retrieval-Augmented Generation) Must have: Understanding of semantic vs lexical search paradigms Must have: Experience with Learning to Rank (LTR) techniques and libraries (e.g., XGBoost, LightGBM with LTR support) Should be proficient in SQL and BigQuery for analytics and feature generation Should have experience with Dataproc clusters for distributed data processing using Apache Spark or PySpark Should have experience deploying models and services using Vertex AI, Cloud Run, or Cloud Functions Should be comfortable working with BM25 ranking (via Elasticsearch or OpenSearch) and blending with vector-based approaches Good to have: Familiarity with Vertex AI Matching Engine for scalable vector retrieval Good to have: Familiarity with TensorFlow Hub, Hugging Face, or other model repositories Good to have: Experience with prompt engineering, context windowing, and embedding optimization for LLM-based systems Should understand how to build end-to-end ML pipelines for search and ranking applications Must have: Awareness of evaluation metrics for search relevance (e.g., precision@k, recall, nDCG, MRR) Should have exposure to CI/CD pipelines and model versioning practices GCP Tools Experience: ML & AI: Vertex AI, Vertex AI Matching Engine, AutoML, AI Platform Storage: BigQuery, Cloud Storage, Firestore Ingestion: Pub/Sub, Cloud Functions, Cloud Run Search: Vector Databases (e.g., Matching Engine, Qdrant on GKE), Elasticsearch/OpenSearch Compute: Cloud Run, Cloud Functions, Vertex Pipelines, Cloud Dataproc (Spark/PySpark) CI/CD & IaC: GitLab/GitHub Actions Location: Remote- Bengaluru,Hyderabad,Delhi / NCR,Chennai,Pune,Kolkata,Ahmedabad,Mumbai

Key Responsibilities: Assist in the design, development, and deployment of Python-based AI/ML models and applications. Work with senior developers and data scientists to preprocess data, train models, and evaluate performance. Write clean, scalable, and efficient Python code for automation, data analysis, and AI pipelines. Participate in brainstorming sessions, code reviews, and team meetings. Document project requirements, processes, and results. Required Skills: Strong foundation in Python programming. Basic understanding of Machine Learning concepts and algorithms. Familiarity with libraries such as NumPy, Pandas, Matplotlib, and scikit-learn. Good analytical and problem-solving skills. Willingness to learn new technologies and take initiative. Good to Have: Exposure to deep learning frameworks like TensorFlow or PyTorch. Experience with Jupyter Notebooks, Git/GitHub, or any version control system. Academic projects or internships related to AI/ML or Python development. Eligibility Criteria: B.E./B.Tech/MCA/M.Sc. in Computer Science, IT, or related field (2023/2024 pass-out preferred). Strong academic track record with a passion for AI and software development. What We Offer: Hands-on experience on real-world AI/ML projects. Mentorship and training by experienced professionals. Dynamic and collaborative work environment. Career growth opportunities in AI and software development domains.