Fram

TNR Tower, 180-192 Nguyen Cong Tru, TP Hồ Chí Minh

Quy mô công ty : 25-99

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Tóm lược

Fram

Duration: Full-time for 6 months

The Role

We’re looking for a Senior Data Scientist who can tackle complex business challenges and transform them into innovative technical solutions. In this role, you’ll dive deep into statistical analysis, data mining, and cutting-edge Large Language Model (LLM) technologies to shape the future of AI-driven products.
You’ll engage hands-on with emerging technologies, pushing the boundaries of what’s possible in AI from early ideation and research through to final delivery. And you will closely collaborate with not only the data team but also product managers and engineers to ensure successful analytics or AI feature execution.

Responsibilities

Human-Centered Analysis: Manipulate human behavior, sentiment, and language data to uncover hidden patterns and support data-driven decision-making.
AI/ML Model Development: Craft effective prompts to interact with AI models, optimizing output quality and relevance, performing fine-tuning, data feeding, validation, and engineering for continuous improvement.
Deliver Pragmatic Solutions: Consistently make pragmatic technical decisions that prioritize business value and speed of delivery, aligning with our early-stage startup environment.
Cross-functional Collaboration: Collaborate with other product and engineering teams to understand data needs and ensure the smooth delivery of data solutions.

5+ years of relevant data science experience, with a strong emphasis on consumer-facing platforms, human-generated data, or equivalent data science domains.
5+ years of experience applying advanced statistical methods and data mining techniques to identify new business opportunities and address existing challenges, including experience building data products from concept to production.
Experience with Natural Language Processing (NLP), AI/Machine Learning (ML), including LLMs and trendy ML models, encompassing prompt engineering, fine-tuning, pipeline setup, validation, and Quality Assurance (QA) for targeted applications.
Expertise in SQL, one or more programming languages (Python, R, C++, Java), and familiarity with data science libraries and toolkits.
Experience translating complex technical concepts to non-technical partners.

Nice to have

Knowledge of Data Engineering, DevOps practices for AI model deployment, and MLOps principles.
AWS Experience: Familiarity with core AWS services used in a data context.
Experience in a Startup Environment: Comfortable with ambiguity and a fast-paced setting.