Data Business Analyst at Morgan Stanley

Budapest, Central Hungary, Hungary -

Full Time

Start Date

Immediate

Expiry Date

09 Feb, 26

Salary

0.0

Posted On

11 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Design Methodologies, Semantic Technologies, Taxonomy Development, Ontology Development, RDF/OWL Concepts, Knowledge Graphs, Semantic Search Engines, Graph Databases, Graph Theory, Natural Language Processing, Machine Learning Integration, Operational Risk Management

Industry

Financial Services

Description

- Support the design of data models including the identification of categorical data - Assist with the design and development of semantic capabilities in partnership with colleagues from Technology and Data-Science teams - Support business partners to leverage data-centric techniques - Manage projects to implement various semantic capabilities such as search utilities, question and answering and recommendation engines. - Bachelor's degree - 4+ years of related experience in a corporation, government body or relevant organization - Analytical mindset with ability to think critically about appropriate solutions to business problems - Demonstrable experience in the use of data led approaches to solving business problems - Analysis of business requirements and subsequent development of data strategies and solutions to address - Strong problem-solving skills for tackling complex data problems in large-scale datasets Skills that will help you in the role: - Experience of data design methodologies and techniques - Practical experience of semantic technologies including taxonomy and ontology development, RDF/OWL concepts, Knowledge Graphs and semantic search engines. - Experience with Knowledge Graphs/ Graph Databases and understanding of Graph Theory concepts - Experience in Natural Language Processing and integrating Machine Learning models with semantic data for classification, inference and recommendation. - Direct experience in operational risk management or related risk domains Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work. To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser. If this role is deemed a Certified role and may require the role holder to hold mandatory regulatory qualifications or the minimum qualifications to meet internal company benchmarks. Flexible work statement Interested in flexible working opportunities? Speak to our recruitment team to find out more. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents.

Responsibilities

The Data Business Analyst will support the design of data models and assist in developing semantic capabilities in collaboration with technology and data science teams. They will manage projects to implement various semantic capabilities such as search utilities and recommendation engines.