Senior Data Scientist
1 week ago
**Background**:
Our Data team is a unified, full-stack group responsible for the entire data science lifecycle. The mission is to deliver end-to-end data science services across the organization - spanning data infrastructure, engineering, advanced analytics, and data visualization.
We adopt a human-centered, data-driven approach to generate talent management and Learning & Development (L&D) insights using AI models and other cutting-edge methods. We value individuals’ perspectives and foster a culture of open communication and collaboration.
**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**: Work with other product and engineering teams to understand data needs and ensure smooth data solution delivery.
**Qualifications**:
- 5+ years of relevant data science experience, with a strong emphasis on consumer-facing platforms, human-generated data, or equivalent data science domains.
- 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.
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