# 18. Data Scientist *Nature of the tasks* * Collect business requirement and develop advanced data mining solutions or identify, assess and deploy relevant existing data mining, machine learning and business intelligence solution * Specification and design of presentation interfaces with optimal usability/user experience * Identify, collect, convert and update different data types/sets in several locations (e.g. ETL) * Produces data models according to specific problems statements. * Scripting and programming. * Contribute to the design and implementation of the analytics architecture and its solution stack (including performance aspects, physical design, capacity dimensions etc...) * Write the different documentation associated with the tasks and liaise with other project teams as necessary to address cross-project interdependencies. *Education* : EQF6 focus on Data management *Specific expertise and technologies* * Excellent knowledge of Data Analytics techniques and tools. * Experience in Machine Learning and Natural Language Processing. * Experience with languages like R, Python, PERL. * Proficient in continuous code delivery and unit testing * Good knowledge of business intelligence tools (Tableau, SAS, SAP, GoodData...) * Expertise in the ETL processes and tools (i.e. Talend Open Studio...) * Good knowledge of SQL tooling (NoSQL DB, MongoDB, Hadoop, SQL) * Knowledge of architectural design and implementation of scalable modern data stores. * Knowledge in one of the following areas: predictive (forecasting, recommendation), prescriptive (simulation), sentiment analysis, topic detection, social media crawling and processing, plagiarism detection, trends/anomalies detection in datasets, recommendation systems *Certification and/or Standards* * Not applicable *Skills* * Ability to work in a team as well as autonomously * Results-oriented mindset, focused on delivering * Good communication skills in English, both orally and in written form *On-call services foreseen for this profile :* No --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://doc.montoyer.com/framework-contracts/digit-tm-ii/digit-tm-ii-profiles-description/18.-data-scientist.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.