Data Scientist

Job Responsibilities of this position :

1. Lead and architect the design and development of AI/ML predictive models that significantly enhance decision-making processes for clients, leveraging their own historical data sets and industry insights.

2. Engage with senior executives and key stakeholders to fully understand their business needs, strategic objectives, and data requirements, ensuring the AI/ML models are precisely tailored to deliver maximum business value.

3. Oversee the implementation, testing, and validation of machine learning algorithms, ensuring that the models are not only accurate but also scalable, reliable, and robust for enterprise-level production environments.

4. Collaborate cross-functionally with product managers, engineers, and data scientists to integrate AI/ML models into Xemplar's product ecosystem, optimizing performance and efficiency across multiple teams.

5. Provide expert analysis and interpretation of complex data sets from various sources, delivering actionable insights that inform business decisions and improve the accuracy and predictive power of models.

6. Stay ahead of emerging AI/ML trends and innovations, actively incorporating cutting-edge research, techniques, and best practices into the modeling and development processes.

7. Drive the technical vision and strategic direction for AI/ML initiatives, mentoring and guiding less experienced team members while also establishing best practices and a culture of continuous improvement.

8. Partner with business analysts, frontend, mid-tier, and backend developers to ensure the development, deployment, and performance of production applications that effectively utilize AI/ML models to deliver real-world impact.

9. Take ownership of solving complex, ambiguous problems with minimal supervision, applying advanced theoretical knowledge to conceptualize, simulate, and implement AI/ML solutions.

10. Define and manage data requirements and data quality assessments, orchestrating the extraction, transformation, and integration of data for analytical and modeling projects.

Required Relevant Experience:

✓ 10+ years of experience in developing and deploying AI/ML predictive models in production environments, with a strong portfolio of successful enterprise-scale projects and solutions.

✓ Expertise in machine learning techniques, including but not limited to regression, classification, clustering, time series analysis, and deep learning.

✓ Advanced proficiency in programming languages such as Python, R, or similar, and mastery of machine learning libraries (e.g., TensorFlow, scikit-learn, PyTorch).

✓ Extensive experience with data wrangling, feature engineering, and working with large, complex, high-volume datasets.

✓ Proven track record in model validation and testing, ensuring models are robust, reliable, and scalable across different use cases and environments.

✓ Deep understanding of the P&C Insurance domain, with specific experience in areas like claims prediction, risk modeling, pricing optimization, and customer segmentation.

✓ Strong ability to communicate complex technical concepts to senior, non-technical stakeholders, influencing decision-making at the highest levels.

✓ Significant hands-on experience working with both structured and unstructured data at scale, with expertise in cloud platforms, distributed computing, and big data technologies.

✓ 10+ years of experience in predictive model development, data mining, statistical modeling, and high-performance computing in complex enterprise environments.