We are dedicated to delivering engaging and original gaming experiences to a worldwide audience, whenever and wherever they choose to play while building a community that fosters inclusivity, connection, and accessibility. Level Infinite also provides a wide range of services and resources to our network of developers and partner studios around the world to help them unlock the true potential of their games.What the Role EntailsWe are looking for an Associate Data Scientist to help build AI-powered capabilities for our influencer marketing platform. This role focuses on turning data and machine learning into practical product features—from creator discovery and content understanding to campaign optimization and performance prediction.
You will work at the intersection of data science, product, and engineering, helping bring intelligent systems into real world use cases that drive measurable business impact.
1. Applied AI & Model Development
Develop and deploy machine learning / AI models to enhance platform capabilities.
Work on use cases such as:
Creator segmentation and recommendation.
Creator Content labeling and data analysis.
Campaign performance prediction and optimization.
Agentic Systems Developing.
2. Problem Framing & Experimentation
Translate business and product problems into data science solutions.
Design experiments to validate hypotheses and measure impact.
Iterate on models based on performance, feedback, and real-world usage.
3. Data Pipeline & Feature Engineering
Work with data engineers to define and build scalable data pipelines.
Clean, process, and structure large datasets (creator data, content metadata, campaign performance).
Design meaningful features that improve model performance.
4. Product Integration
Collaborate closely with product managers and engineers to integrate models into the platform.
Ensure models are production-ready, reliable, and scalable.
Contribute to API design, model serving, and inference workflows.
5. Monitoring & Continuous Improvement
Track model performance using appropriate metrics (accuracy, precision, recall, business KPIs).
Maintain documentation and ensure reproducibility.
Core Values
Integrity – You prioritize correctness, transparency, and responsible use of data.
Gamer Native – You understand gaming ecosystems and player/content dynamics.
Pop Culture Fluent – You are familiar with creators, platforms, and digital trends.
Tech-Savvy – You are curious and hands-on with emerging AI technologies.
Technical Skills
Strong foundation in machine learning and statistics.
Proficiency in Python and common ML libraries (e.g., PyTorch,scikit-learn).
Experience with data processing (e.g., pandas, SQL).
Familiarity with LLMs, NLP, or recommendation systems is a strong plus.
Understanding of model deployment (APIs, batch/real-time inference) is preferred.
Data & Product Thinking
Ability to translate ambiguous business problems into data science solutions.
Strong analytical thinking and hypothesis-driven approach.
Understanding of how models create value in a product context (not just offline metrics).
Execution & Collaboration
Ability to work cross-functionally with product, engineering, and business teams.
Good communication skills—able to explain complex models in simple terms.
Strong ownership and ability to iterate quickly.
Nice to Have
Experience in influencer marketing, advertising, or creator platforms.
Familiarity with social media data (e.g., YouTube, Twitch, TikTok ecosystems).
Experience with embeddings, vector databases, or retrieval systems.
Basic knowledge of data engineering or MLOps workflows.
Example Projects You Might Work On
Build a creator discovery engine using embeddings + similarity search.
Develop a content understanding pipeline (tags, sentiment, brand safety).
Train a campaign ROI prediction model to guide budget allocation.
Integrate LLMs to improve tool efficiency and automate workflows.
As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.
Skills Required
- Strong foundation in machine learning and statistics
- Proficiency in Python and common ML libraries
- Experience with data processing (e.g., pandas, SQL)
Tencent Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Tencent and has not been reviewed or approved by Tencent.
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Healthcare Strength — Healthcare coverage is positioned as a standout, with strong PPO options and relatively low prescription costs highlighted for U.S. plans. This suggests the medical offering can be a meaningful component of the overall rewards package for U.S.-based employees.
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Retirement Support — Retirement support is framed as competitive in the U.S., with employer match details called out as an item to confirm in writing. This indicates retirement benefits can be a notable strength where applicable.
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Strong & Reliable Incentives — Performance-linked incentives and share-based awards are repeatedly included as part of the compensation model, alongside potential RSU and sign-on eligibility in certain roles. This points to total rewards often extending beyond base pay through variable and equity components.
Tencent Insights
What We Do
Tencent uses technology to enrich the lives of Internet users. Our communications and social platforms Weixin and QQ connect users with each other, with digital content and daily life services in just a few clicks. Our high performance advertising platform helps brands and marketers reach out to hundreds of millions of consumers in China. Our financial technology and business services support our partners' business growth and assist their digital upgrade. We invest heavily in talent and technological innovation, actively participating in the development of the Internet industry. Tencent was founded in Shenzhen, China, in 1998, and listed on the Main Board of the Stock Exchange of Hong Kong since June 2004.
