Manager-Data Analytics
Manager-Data Analytics
Posted on :
02-04-2025
Employer Active
1 Vacancy
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Job Description
Job Description
Sutherland is seeking an organized and reliable person to join us as a Manager Data Science. We are a group of driven and supportive individuals. If you are looking to build a fulfilling career and are confident you have the skills and experience to help us succeed we want to work with you!
Manager Responsibilities:
- Data Analytics and Insights:
- Conduct analytics to identify patterns and generate actionable insights to support strategic decisions.
- Process Unstructured data to drive actionable insights.
- Translate quantitative analyses into comprehensive visuals and reports for nontechnical audiences.
- Model Development and Validation:
- Build validate measure and retrain machine learning models including supervised and unsupervised algorithms.
- Apply expertise in Natural Language Processing (NLP) and Generative AI to solve complex business challenges.
- Deployment and Collaboration:
- Collaborate with AI Engineers to deploy machine learning models and set up inference processes.
- Ensure models are scalable maintainable and aligned with organizational goals.
- What Will you focus on :
- Risk Assessment and Pricing: Developing predictive models to evaluate risks and set accurate premiums. By analyzing historical data they identify patterns that inform underwriting decisions.
- Fraud Detection: Implementing machine learning algorithms to detect fraudulent activities by identifying anomalies in claims data. This proactive approach helps in minimizing losses due to fraud.
- Customer Segmentation and Personalization: Analyzing customer data to segment the market and tailor insurance products to specific groups enhancing customer satisfaction and retention.
- Claims Management Optimization: Utilizing data analytics to streamline the claims process ensuring timely and accurate settlements. This includes predicting claim volumes and identifying potential bottlenecks.
- Marketing Strategy Enhancement: Assessing the effectiveness of marketing campaigns and identifying opportunities for customer acquisition and retention
Requirements:
- Experience: 67 years of experience in Insurance analytics or a related domain
- Education: bachelors degree in Engineering Statistics Mathematics Computer Science or a related quantitative field.
- Proficiency in programming languages and data analysis tools such as Python R PySpark and SQL.
- Solid experience in developing predictive modeling techniques (lookalike models time series forecasting regression clustering)
- Ability to design implement and refine business rules for optimizing the Claims and Underwriting value chains is a good to have.
- Familiarity with working in cloud environment (AWS/ AZURE) using distributed compute for large datasets and version control tools (eg Git)
- Data Proficiency: Expertise in handling largescale Insurance datasets and applying statistical and machine learning methods to drive actionable insights.
- Data Storytelling & Communication: Demonstrated ability to translate complex data insights into clear compelling narratives and presentations. Adept at communicating technical findings in a relatable manner to nontechnical stakeholders.
- Autonomy & Prioritization: Proven ability to work independently manage multiple projects/workstreams and prioritize effectively in a fastpaced datadriven environment.
- ProblemSolving & Collaboration: Demonstrated ability to troubleshoot complex data issues optimize system performance and work effectively within a team environment.
Qualifications :
Requirements:
- Experience: 67 years of experience in Insurance analytics or a related domain
- Education: bachelors degree in Engineering Statistics Mathematics Computer Science or a related quantitative field.
- Proficiency in programming languages and data analysis tools such as Python R PySpark and SQL.
- Solid experience in developing predictive modeling techniques (lookalike models time series forecasting regression clustering)
- Ability to design implement and refine business rules for optimizing the Claims and Underwriting value chains is a good to have.
- Familiarity with working in cloud environment (AWS/ AZURE) using distributed compute for large datasets and version control tools (eg Git)
- Data Proficiency: Expertise in handling largescale Insurance datasets and applying statistical and machine learning methods to drive actionable insights.
- Data Storytelling & Communication: Demonstrated ability to translate complex data insights into clear compelling narratives and presentations. Adept at communicating technical findings in a relatable manner to nontechnical stakeholders.
- Autonomy & Prioritization: Proven ability to work independently manage multiple projects/workstreams and prioritize effectively in a fastpaced datadriven environment.
- ProblemSolving & Collaboration: Demonstrated ability to troubleshoot complex data issues optimize system performance and work effectively within a team environment.
Additional Information :
All your information will be kept confidential according to EEO guidelines.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
Key Skills
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