Data Scientist

Must Have Skills:

1. Machine learning techniques: regression, classification, clustering, deep learning
2. Programming languages: Python, R
3. Machine learning libraries: TensorFlow, scikit-learn, PyTorch
4. Data wrangling, feature engineering
5. Model validation and testing
6. Cloud platforms, distributed computing, big data technologies

Nice to Have Skills:

1. Knowledge of P&C Insurance domain
2. Experience working with US-based customers
3. Experience in leading teams or projects
4. Experience with high-performance computing
5. GenAi Skills, Experience with LLMs.

Job Responsibilities of this position:

1. 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.

Required Relevant Experience:

1. 5+ 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.
2. Expertise in machine learning techniques, including but not limited to regression, classification, clustering, time series analysis, and deep learning.
3. Advanced proficiency in programming languages such as Python, R, or similar, and mastery of machine learning libraries (e.g., TensorFlow, scikit-learn, PyTorch).
4. Extensive experience with data wrangling, feature engineering, and working with large, complex, high-volume datasets.
5. Proven track record in model validation and testing, ensuring models are robust, reliable, and scalable across different use cases and environments.
6. Deep understanding of the P&C Insurance domain, with specific experience in areaslike claims prediction, risk modeling, pricing optimization, and customer segmentation.
7. Strong ability to communicate complex technical concepts to senior, non-technical stakeholders, influencing decision-making at the highest levels.
8. Significant hands-on experience working with both structured and unstructured data atscale, with expertise in cloud platforms, distributed computing, and big data technologies.
9. 5+ years of experience in predictive model development, data mining, statistical modeling, and high-performance computing in complex enterprise environments.

Years of experience required:

Location:

Mode of work: