Entreprise: ORANGE
Niveau d'etude: Non precise
Localité: INDE / New Delhi
Date limite: 2024-05-31
Recrutement de 01 Sr. Data Scientist
CDI - Sr. Data Scientist
Sr. Data Scientist
Ref :579734 | 09 mai 2024
Date limite de candidature : 31 mai 2024
Votre rôle
Interlock with project product owners to deliver business requirements.
Selecting features, building and optimizing classifiers using machine learning techniques.
Discover the information hidden in vast amounts of data.
Data mining using state-of-the-art methods.
Design, implement & evaluate new techniques and models of data science - data mining, text mining, statistical analysis, machine learning and predictive analytics techniques… - to solve our unique set of problems.
Enhancing data collection procedures to include information that is relevant for building analytic systems.
Have the ability to design, develop & demonstrate the technical solution/models towards achieving use case success criteria.
Processing, cleaning and verifying the integrity of data used for analysis with ML features and modeling.
Have the project management skills in agile environment to lead & drive execution of various use cases/projects towards closure & benefits realization.
Independent Digital and Data Project handing with stakeholders.
Work closely with core development teams to deploy models and technical solutions seamlessly into our production system.
Create, implement and code data science and machine learning model in order to solve the operational issue and help company make smarter decisions
Build new tools to improve our data science pipeline from exploration to production.
Evaluate new Machine Learning technologies, Deep Learning, AutoML, Anomaly Detection, Event Correlation, Root Cause Analysis.
Help the company make smarter decisions based on information gathered.
Doing ad-hoc analysis and presenting results in a clear manner.
Investigate and consolidate new data sources from different OBS tools and systems, prepare the data, evaluate and guarantee their quality and relevance by applying cleaning / filtering.
Write, test and maintain reusable and high-quality code (scripts, APIs, programs) to retrieve and analyse data using data mining, model building, and other analytical techniques for efficient data processing/consolidation and user-friendly data visualization.
Work with OBS and CSO (Int’l and France) team members and end users to mock-up, specify and define Digital and Data use case requirement or analytical request.
Assist in development of AI and ML use cases to support more in depth value added analytics.
Develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity.
Builds and maintains common data layer in partnership with IT.
Ability to clearly understand and document problem statement or use case definition and present it, clarify it with business while attaching business value in numbers to each use case..
Presentation of the analysis to the stackeholder, with a good level of understanding and explainability
Defines company data assets jobs to populate data models.
Automates data flows via ETL processes.
Ability to explore data sets and work to provision them & engage in Exploratory Data Analysis.
Have the expertise to evaluate various techniques, models, analysis to address a specific use case and perform a selection most appropriate to the use case.
Data ready for analysis avoiding biais
Modelisation (Data Science) + ML OPS implementation (ML Engineer)
To guarantee not only the AI value in GDOOPS model
Votre profil
Minimum 3 years expereince as Data Scientist/ML Engineer
Experience with data visualization tools, such as D3.js, GGplot etc
Experience with common data science toolkits, such as R, NumPy, MatLab, Dataiku etc
Knowledge of TensorFlow, MATLAB, Deep Learning, K-nearest neighbors, Random Forests, Naive Bayes, Regression Models. PyTorch. Experience in Generative AI/LLM based RAG implementation.
Le plus de l'offre
Knowledge of SQL and NoSQL databases
Great communication skills
Excellent understanding of machine learning techniques and algorithms
Proficiency in using query languages such as SQL, Hive, R and Python
Good applied statistics skills, such as distributions, statistical testing, regression etc
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