
Leading company in the financial services industry
NFR Semantic Solutions, Associate , LCD Data and Analytics
必須スキル
Python
Data Science
NLP
Machine Learning
Ontology Modeling
Knowledge Graphs
Agile
We're seeking someone to join our team as a Associate in Legal and Compliance Division. This team supports critical NFR activities, such as risk identification, assessment, and management, by developing capabilities based on a blend of symbolic and statistical AI
In the Legal & Compliance division, we assist the Firm in achieving its business objectives by facilitating and overseeing the Firm's management of legal, regulatory and franchise risk. This is an Associate level position within the NFR Data & Analytics is a team in LCDCoE to contribute to a number of innovative projects utilizing semantics, natural language processing, machine learning, and other cutting edge technological approaches. This is an opportunity to learn about and contribute to the next generation of risk technology. The selected candidate would fill a key role and have the opportunity to work closely with global business process owners, technology service providers, and key stakeholders across the Firm
Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.
What you'll do in the role:
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Architect and implement machine assisted semantic capabilities that leverage Natural Language Processing (NLP), Data Science, Knowledge Graph reasoning and AI/ML based techniques to execute the NFR Data Strategy.
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Develop and enhance core semantic functionalities (semantic search, recommendations, classification, auto-categorization, similarity detection, and semantic enrichment) powered by NLP, ML, and/or LLM based techniques
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Partner extensively with product owners, framework teams and SMEs to translate business requirements into clear modeling needs aligned with underlying semantic assets, including ontologies, taxonomies, and other graph models.
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Work with platforms such as Metaphactory, helping design SPARQL-powered cached queries and views, knowledge panels, and user-facing semantic explorations.
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Collaborate with Technology teams to deploy and orchestrate solutions that are graph-compatible
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Maintain clear technical documentation of modeling decisions, data needs, core logics, evaluation methodologies, and audit ready artifacts.
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Ensure adherence to model governance, documentation, monitoring, and other compliance requirements throughout the solution lifecycle.
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Contribute to internal best-practices on semantic modeling, NLP/AI advancements, dataset onboarding and quality assurance
What you'll bring to the role:
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At least 2 years of professional experience in financial services or similarly regulated industries, with exposure to risk, compliance, operations, or other domains requiring strong control and governance sensitivity.
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Strong technical background in data science, NLP, machine learning, ontologies, or semantic architecture-with some hands-on experience in ontology modeling, knowledge graphs.
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Solid programming skills in Python (or similar languages) with the ability to build automation, craft SPARQL queries, develop and deploy NLP models, aligned to semantic and ontology structures.
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Foundational understanding of Non Financial Risk (NFR) concepts or experience in adjacent disciplines such as Operations, Finance, Compliance, or Enterprise Risk Management is also good to have.
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Experience delivering solutions in Agile environments, including refining requirements, managing iterative development cycles, conducting user acceptance testing, gathering stakeholder feedback, and supporting production rollout.
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Exposure to data management, data governance, or information management practices, including an understanding of data quality, metadata, lineage, and controls.
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Desirable to have: familiarity with semantic platforms (e.g., Metaphactory), prompt engineering, AI/ML based solutions, GraphDB, or data engineering concepts.
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Additional Requirements & Skills
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Bachelor's degree or equivalent experience.
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Excellent interpersonal skills, including the ability to work as part of a team and delegate tasks.
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Must be a self-starter and highly organized; attention to detail is a must.
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Excellent analytical skills required along with strong written and verbal communication skills.
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Should be prepared to become proficient with several semantic applications and standards, including semantic platforms (e.g., Metaphactory, Stardog, GraphDB), SPARQL, RDF, and OWL. Existing proficiency is not required but must demonstrate the capability to learn them.
WHAT YOU CAN EXPECT FROM MORGAN STANLEY:
At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 years. 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. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. 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.
Morgan Stanley is an equal opportunities employer. 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.
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Morgan Stanleyについて

Morgan Stanley
PublicMorgan Stanley is an American multinational investment bank and financial services company headquartered at 1585 Broadway in Midtown Manhattan, New York City.
10,001+
従業員数
New York
本社所在地
$150B
企業価値
レビュー
10件のレビュー
4.1
10件のレビュー
ワークライフバランス
2.8
報酬
4.2
企業文化
3.7
キャリア
4.1
経営陣
2.9
75%
知人への推奨率
良い点
Great learning opportunities and experience
High salary and bonuses
Good team dynamics and supportive colleagues
改善点
Long hours during peak times
High stress and overwhelming environment
Work-life balance issues
給与レンジ
6,221件のデータ
Junior/L3
Director
Junior/L3 · Operations Analyst
441件のレポート
$83,240
年収総額
基本給
$76,802
ストック
-
ボーナス
$6,438
$60,778
$115,186
面接レビュー
レビュー6件
難易度
3.2
/ 5
期間
21-35週間
面接プロセス
1
Application Review
2
HR Screen/HireVue
3
Technical/Behavioral Interviews
4
Superday/Final Round
5
Onsite Interview
6
Offer Decision
よくある質問
Technical Knowledge
Behavioral/STAR
Investment/Finance Concepts
Case Study
Culture Fit
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