Data Scientist (Hybrid)

TSC.ai; Singapore; Hybrid; SGD 60,000 - 80,000; Full time

Job summary

A global AI firm is seeking a dedicated data scientist to create data science applications and enhance data technologies. The ideal candidate will have a strong foundation in Python and SQL, as well as experience with graph analytics and machine learning. You'll work closely with product teams and have the opportunity for mentorship and growth in a hybrid role. This position offers a dynamic team culture and a commitment to employee development.

Benefits

Fast-track learning

Mentorship from leadership

20 days annual leave

International opportunities

Qualifications

• Passion for data science and big data technologies.
• Comfort working with large-scale datasets in production.
• Proficiency in Python and SQL is required.

Responsibilities

• Collaborate with product and engineering teams to create data science applications.
• Research and validate advancements in graph mining and analytics.
• Document and validate developed applications prior to deployment.

Skills

Data science

Graph analytics

Machine learning algorithms

Natural language processing

Python

SQL

Tools

JavaScript

TypeScript

Job description

About TSC

The Stakeholder Company (TSC) is a global artificial intelligence (AI) firm at the forefront of AI-native stakeholder relationship management. Our flagship solution, Genie, delivers comprehensive and in-depth situational awareness through advanced open-source monitoring, seamlessly complementing existing stakeholder monitoring and engagement workflows. Genie leverages a sophisticated AI ecosystem to intelligently filter online news sources, extracting events relevant to the millions of stakeholders it tracks. We proudly serve Fortune 500 companies and leading NGOs worldwide, operating in over 95 countries and across 20+ industries.

What we do:

Our data science applications are designed to empower users to monitor media trends, track developing conversations, and gain insights into stakeholders. We utilize natural language processing tools for text classification and media item recommendations, as well as to extract stakeholder information that complements data curated by our specialists. Through graph analytics, we are developing tools to uncover insights from complex stakeholder relationship data, assessing their relevance and importance to Genie users. Our in-house RAG engine transforms this curated data into highly contextualized insights for recommendation, monitoring, and analysis, seamlessly integrated with user workflows. Our overarching goal is to provide an intelligent and seamless user experience.

About the role:

Passion and work ethic are our priority. We are looking for someone who has seen what AI and machine learning can do and is excited by the opportunities available. Qualifications are secondary, but we expect you to demonstrate the tenacity to overcome a steep learning curve and the humility to learn from people of diverse backgrounds. You are not afraid to speak your mind in discussions, and we can rely on you to provide considered, substantive, and practical ideas.

Key Responsibilities:

• Collaborate closely with product and engineering teams to translate complex business problems into production-ready data science applications.
• Research, enhance, and validate state-of-the-art technologies, with a particular focus on advancements in graph mining, graph analytics, and natural language processing.
• Ensure rigorous documentation and validation of all developed applications prior to deployment.
  
  
  

What Were Looking For:

• A profound passion for data science and big data technologies, coupled with a commitment to continuous learning and staying abreast of industry advancements.
• Demonstrated comfort working with large-scale datasets in production.
• Exceptional ability to articulate complex data science concepts clearly and concisely to diverse audiences.
• Proficiency in common machine learning and deep learning algorithms, including a solid understanding of various optimization and loss functions.
• Expertise in common graph mining and analytics techniques, including community detection, recommendation systems, label propagation, and various classification tasks.
• Familiarity with standard text processing techniques.
• Proficiency in Python and SQL is required. Experience with additional languages such as TypeScript, JavaScript is a plus.
• Familiarity with agent toolkits and frameworks like Langgraph, CrewAI.
• Familiarity with data processing toolkits, libraries, and approaches for handling large text or graph datasets.
  
  
  

Things you should expect from TSC:

• We strive to be the best place you will ever work for;
• Fast-track learning through exposure to various roles across the organization;
• Honed skill sets;
• Direct access, respect, and mentoring from the leadership with an interest in your development.
• Hybrid working arrangement (3 days WFO, 2 days WFH)
• Annual leave: 20 days per year
• International opportunity to expose and grow
• Other benefits to be shared in the interview
  
  
  

Team Culture - How do you find yourself fitting in our team:

• Intellectual curiosity for the world around you, technology, and our clients' needs
• Solid general knowledge and skills in your core area
• Excellent problem-solving capabilities and adaptability
• Enthusiasm for finding elegant, pragmatic solutions
• Team player were a small, close-knit team and excellence is expected, as is the capability to take on and own big challenges, solving conventional challenges in unconventional ways, all without losing your sense of humor and fun
  
  
  

Hiring Process: The result of each interview round will be provided within 1 - 2 weeks.

• 1st round - Online HR interview: 30 minutes
• 2nd round - Take-home Assignment: to be delivered within 48 hours
• 3rd round - Technical Interview: 1 hour
• Final round - Culture-fit interview: 1 hour
• Background checks
  
  
  

We are an equal opportunity employer and welcome applications from all qualified individuals regardless of age, race, nationality, gender, religion, marital status, family responsibilities, or disability. Selection will be based on merit and in accordance with the Tripartite Guidelines on Fair Employment Practices.