Lead Data Scientist

Data scientist who can think out of the box and expects more from their career.

• Research business domain and develop use-cases to support enterprise-wide AI/ML solutions.
• Model design, feature planning, system infrastructure, production setup and monitoring, and release management.
• Excellent understanding of machine learning techniques and algorithms, such as SVM, Decision Forests, k-NN, Naive Bayes etc.
• Experience in selecting features, building and optimizing classifiers using machine learning techniques.
• Prior experience with data visualization tools, such as D3.js, GGplot, etc..
• Good knowledge on statistics skills, such as distributions, statistical testing, regression, etc..
• Adequate presentation and communication skills to explain results and methodologies to non-technical stakeholders.
• Test, troubleshoot and enhance the developed models in a distributed environments to improve it's accuracy.
• Work closely with product teams to implement algorithms with Python and/or R.
• Design and implement scalable predictive models, classifiers leveraging machine learning, data regression.
• Facilitate integration with enterprise applications using APIs to enrich implementations.

Profile Required:

• Minimum 5 years of experience in designing/developing industrial IT solutions with Data Science
• Minimum 3-5 years of experience in developing and deploying machine learning, deep learning, NLP solutions.
• Very strong grasp of IT concepts with a strong algorithms/data structures background.
• Background building systems with a major machine learning libraries strong proficiency with libraries like scikit-learn, pandas, PyTorch/TensorFlow.
• Background in applying deep learning to real problems and knowledge of a major framework
• Experience with common data science toolkits, such as Scikit, NumPy, R libraries - Excellence in at least one of these is mandatory.
• Proficiency with any one NoSQL databases such as MongoDB, Cassandra, HBase.
• Should have prior experience in developing APIs, services using either C# or Java.
• Should have good awareness on entire machine learning/ predictive modeling & implementation.
• Proficient in Python, API integration, and ML libraries like Hugging Face Transformers, LangChain, and OpenAI API.
• Strong understanding of NLP techniques and model evaluation metrics.
• Experience deploying GenAI solutions in cloud environments (AWS/GCP/Azure).
• Familiarity with prompt tuning, RAG, embeddings, and vector stores.
• practical knowledge of MLOps practices (model versioning, deployment pipelines, monitoring).
• Hands on Experience in CI/CD , Devops Principle .

Specific Context

Opportunity to work with some of the best minds in a team and learn a lot on the technical front. Get mentored/groomed on the best practices followed in the software industry.

"Internal Interfaces:

- Team members, Technical leader, Business Analyst, Product Owners,

External Interfaces:

- Onshore team, Developers, Technical Lead, Business Analyst, End Users"

Environment

At Société Générale, we are convinced that people are drivers of change, and that the world of tomorrow will be shaped by all their initiatives, from the smallest to the most ambitious. Whether you're joining us for a period of months, years or your entire career, together we can have a positive impact on the future. Creating, daring, innovating, and taking action are part of our DNA. If you too want to be directly involved, grow in a stimulating and caring environment, feel useful on a daily basis and develop or strengthen your expertise, you will feel right at home with us

Still hesitating?

You should know that our employees can dedicate several days per year to solidarity actions during their working hours, including sponsoring people struggling with their orientation or professional integration, participating in the financial education of young apprentices, and sharing their skills with charities. There are many ways to get involved.

We are committed to support accelerating our Group's ESG strategy by implementing ESG principles in all our activities and policies. They are translated in our business activity (ESG assessment, reporting, project management or IT activities), our work environment and in our responsible practices for environment protection.

Why Join Us

"We are committed to creating a diverse environment and are proud to be an equal opportunity employer. All qualified applicants receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status".