Summary: The Senior Data Scientist will design, develop, and deploy advanced analytics, Generative AI, and LLM solutions to convert business challenges into valuable data products, directly impacting FCE's operations and efficiency.
Responsibilities:
- Lead end-to-end AI and data science projects.
- Design, prototype and industrialize Generative AI and LLM solutions.
- Develop robust LLM pipelines and predictive models.
- Apply machine learning and AI techniques to various use cases.
- Collaborate with data engineers on scalable data pipeline definitions.
- Ensure production readiness of AI solutions and monitor their performance.
- Translate business needs into analytical approaches and recommendations.
- Mentor junior team members and support knowledge transfer.
- Communicate outcomes effectively to stakeholders with clear storytelling.
Must Haves:
- Master's or Engineering degree in Computer Science, Data Science or related field; PhD is a plus.
- A minimum of 5 years experience in a data-focused role (Data Scientist, Machine Learning Engineer, etc.).
- Strong proficiency in Python, with knowledge of PySpark/Spark and SQL.
- Experience with machine learning algorithms and deep learning techniques.
- Hands-on experience with Generative AI and LLM development.
- Experience with data quality management and scalable data pipelines.
- Familiarity with cloud and enterprise data platforms; experience with Palantir Foundry is advantageous.
- Strong problem-solving skills and ability to manage priorities.
- Exceptional communication and presentation skills.
Nice to Haves:
- Experience delivering AI solutions for automotive or manufacturing use cases.
- Exposure to cybersecurity and responsible AI practices.
- Ability to define measurable business value and operational impact from AI solutions.
Other Details:
- Category 1: Working Environment: International collaboration with cross-functional teams.
- Category 2: Role Focus: Digital transformation through AI and advanced analytics.
Reason (Must Have):
- Master's Degree: Essential for understanding complex algorithms and data analysis techniques, ensuring quality in model development.
- 5 Years Experience: Necessary to handle the depth of AI projects and guide less experienced team members effectively.
- Python Proficiency: Critical for developing and deploying production-grade machine learning solutions.
Reason (Nice to Have):
- Domain Experience: Valuable for tailoring AI solutions to specific industry needs, increasing adoption and impact.
- Cobalt Experience: Enhances the ability to build robust, scalable applications that align with enterprise requirements.
Trust Score: Score: High
Evidence: The job description is detailed with clear responsibilities, specific qualifications, skills required, and contextual information, allowing for effective candidate sourcing.
Sourcing Guidance:
The job description provides good technical clarity for sourcing. Consider these potential recommendations to enhance the search:
- Recommendation: Search for candidates with experience in both AI and data engineering.
Rationale: Candidates with a blended skill set in AI and data engineering will likely succeed in developing robust solutions as described in the role.
- Recommendation: Focus on candidates with experience in the automotive industry.
Rationale: Relevant domain expertise will ensure a faster ramp-up and greater impact given the specialized applications of AI in automotive contexts.
- Recommendation: Consider flexibility on the must-have years of experience for high-potential candidates.
Rationale: Allowing for slightly less experience might attract candidates with strong project work who can bring innovative perspectives to the role.
