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Posted 03 June, 2026

Proximus_Analytics_Day0 Req- Data science and Machine Learning

ClifyX
India Full Time
Reference: 365_594563_26-00757
  1. REQUIREMENT TEMPLATE – Skill name
No. of positions 3
Prepared by
Account Name DNA Analytics - ANADU01
Service Line Analytics
Must have skills - 2 skills which are non-negotiable Data science and Machine Learning
Desirable skills - 1 skill which is nice to have ETL Development
Infosys role Lead Analyst Data science
Desired experience range Total should be 10+ and relevant should be 3+
Location(s) where this position can work out of Bangalore
Does this position require working from client office all or some days in the week? If yes pls provide details Yes Working from Client location is Mandatory.
3 days in a week from Client office and 2 days WFH.
Is remote working allowed Not allowed
Any additional things to be checked
Responsibilities and JD in brief along with additional criteria to be considered (if any):
Within this Proximus' first Belgian center of excellence combining artificial intelligence and cybersecurity, as a Data Scientist, you will play a key role in developing AI solutions for the Proximus Group and its partners. By taking up a use case right from the start you will explore and understand the data, pick the right ML solution and technology as well as ensure development of a working prototype (MVP) to show the value to our customers. For successful investigation you will go further with integration and deployment of your solution to production. You will do so while ensuring that our internal governance processes and best practices are respected. You will also collaborate with other team members in knowledge sharing as well as continuously improving our way of working.
Responsibilities
  • Translate business requests into data requirements, extract the required structured and unstructured data and prepare large-scale datasets for modelling
  • Identify high-value use cases through data exploration and visualization
  • Develop AI applications using state-of-the-art (Gen)AI technology
  • Come up with concrete prototypes (MVP) to demonstrate their value to the customer
  • Deploy prototypes to production, with support of Tech enabler team & IT, to obtain reliable, scalable systems
  • Present your results in a clear manner and discuss them with multi-functional project teams
  • Work in close collaboration with business experts (e.g. for requirement gathering, data source identification, data and process understanding, feature engineering, result validation, etc.), with IT (e.g. for ETL, deployment to production, etc.) and with other AI engineers in the team (e.g. for knowledge sharing).

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