Overview:
We are seeking a highly skilled and dynamic Data Scientist with a strong background in applied research and a passion for exploring cutting-edge technologies in the field of AI. The ideal candidate will not only possess advanced analytical and technical skills but also excel in consulting and due diligence, playing a crucial role in identifying and integrating innovative AI technologies into our organization. The candidate should have broad knowledge and experience in generative AI in the natural language, image, video, and other application domains.
Responsibilities:
Applied Research:
- Conduct in-depth research to identify and understand industry trends, emerging technologies, and best practices in data science and AI.
- Collaborate with cross-functional teams to design and implement practical data-driven solutions that address real-world challenges and drive business outcomes.
- Identify, research, and develop new capabilities and functionality into Aicadium products, in the domains of Industrial Computer Vision and Multimodal Foundation models.
Consulting:
- Engage with internal and external stakeholders to understand their business needs and challenges, providing strategic guidance on leveraging data science and AI for optimal outcomes.
- Act as a consultant, translating complex technical concepts into actionable insights for non-technical audiences.
Technology Exploration:
- Stay abreast of the latest advancements in AI and data science, actively exploring and evaluating new technologies to enhance our organization's capabilities.
- Collaborate with internal teams to identify areas where innovative technologies can be applied to solve existing problems or create new opportunities.
- Help drive innovation and new technology adoption within Aicadium.
Proof-of-Concept (POC) Development:
- Rapidly develop POCs utilizing new Generative AI technologies and models.
- These POCs will involve use case discovery, implementation, and testing of Generative AI models, frameworks, or platforms to evaluate their feasibility and potential impact.
- The applied research team will deliver functional prototypes and concise reports summarizing the POC results, including insights on the technology's applicability, limitations, and potential commercial value.
Due Diligence:
- Conduct thorough due diligence on potential AI technologies and solutions, assessing their feasibility, scalability, and alignment with organizational goals.
- Collaborate with legal and compliance teams to ensure adherence to regulatory requirements and ethical considerations.
Collaboration:
- Work closely with cross-functional teams, including engineers, product managers, and business analysts, to integrate data-driven solutions into existing systems and processes.
- Foster a collaborative and innovative environment by sharing knowledge, insights, and best practices with team members.
Qualifications:
- Master's or Ph.D. in a quantitative field such as ML, Computer Science, Statistics, Mathematics, Physics, or a related discipline.
- Proven experience in applied research, focusing on developing and implementing efficient data-driven solutions.
- Broad knowledge and hands-on experience with generative AI approaches and technologies.
- Deep technical understanding of generative AI models, frameworks, libraries, and tools; their capabilities and limitations, data requirements, training, management, software infrastructure, scalability, security, and technical viability.
- Demonstrated ability to communicate complex technical concepts to non-technical stakeholders effectively.
- Strong analytical and problem-solving skills, keen interest in exploring, testing, and adopting new technologies.
- Keen interest in the latest developments in AI and ML, and a strong ability to distinguish truth from hype.
- Strong programming skills in Python and modern ML frameworks.
- Strong background in modern and emerging ML methods and architectures.
- Experience in due diligence and technology assessment in the AI domain is highly desirable.
- Experience in consulting is highly desirable.
