Job Title: Associate Director at Stelfox
Lead Data Scientist - Contractor Position - Daily Rates - Hybrid-Working Model
This is an excellent contractor position that has just opened with a global company to work within their Data & Analytics Engineering team.
Candidates must be based in Ireland and have full working rights.
Key Responsibilities:
* Apply data science techniques to solve business problems across a broad range of data analysis functions, including predictive analysis, data modeling, visualization, and data profiling.
* Utilize multiple sources of data, including structured and unstructured data, along with a broad range of machine learning techniques to improve insights into the models.
* Support the development of new modeling techniques and procedures.
* Develop and maintain high-quality, robust predictive models and AI solutions using advanced analytic techniques.
* Extract and analyze internal and external data sources to help answer key business problems related to risk assessment.
* Interpret data and ML models outputs and provide clear, actionable insights and recommendations.
Required Skills:
* A strong knowledge of statistical and data science techniques, including machine learning, data visualization, A/B testing, and experience with databases.
* Proficiency in a broad range of data science programming languages, applications, and data environments (e.g., Python, R, SQL).
* Experience with machine learning frameworks and libraries.
* A commitment to data compliance, model governance, and security protocols.
* Strong business acumen to understand why and how the work we do will impact our business stakeholders.
* Strong problem-solving skills and effective communication, with an ability to explain technical concepts to a non-technical audience.
* A Bachelor's, Master's, or Ph.D. in a statistical, mathematical, or technical field (e.g., computer science, actuarial science).
* 5+ years of experience in developing and implementing data science techniques.
* Demonstrated academic or industry experience with generative AI, including prompt engineering, RAG workflows, and integrating LLMs into business processes.
* Familiarity with MLOps practices, including model deployment, monitoring, and lifecycle management.