Remote Insurance Data Scientist

Placements24; East London; Hybrid; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Fully remote

Flexible schedule

Health, dental and vision insurance

Professional development

Job summary

Placements24 is seeking a talented Remote Insurance Data Scientist to join a progressive, fully remote team. You will leverage advanced analytics, machine learning, and statistical modeling to drive insights, improve products, and optimize operations within the insurance domain.

The ideal candidate has a strong data science background, 4+ years in the field, and is comfortable translating complex findings into actionable business strategies from a distributed work environment.

Qualifications

• Master's or PhD in a quantitative field and at least 4 years of data science experience in insurance or financial services.
• Proficiency in Python or R with strong ML library experience (Scikit-learn, TensorFlow, PyTorch) and SQL.
• Experience with big data tech (Spark, Hadoop) and ability to work remotely.

Responsibilities

• Develop and implement statistical models and ML algorithms for insurance data.
• Extract, clean, and transform large, complex datasets.
• Identify trends for pricing, underwriting, fraud detection, and engagement.
• Design and run A/B tests and experiments.
• Build predictive models for churn, risk, and lifetime value.
• Communicate findings to technical and non-technical stakeholders.

Skills

Python

R

Scikit-learn

TensorFlow

PyTorch

SQL

Big data: Spark/Hadoop

Data visualization

Remote work discipline

Education

Master's degree in Data Science/Statistics/CS

PhD in a quantitative field

Tools

Spark

Hadoop

Jupyter

Job description

About the Role

Our client, a progressive insurance company known for its innovative approach, is actively seeking a talented and experienced Remote Insurance Data Scientist to join their forward-thinking, entirely remote team. This role is integral to leveraging advanced data analytics, machine learning, and statistical modeling to drive business insights, enhance product offerings, and optimize operational efficiency. The ideal candidate will have a strong background in data science, a passion for uncovering patterns in complex datasets, and the ability to translate findings into actionable strategies within the insurance domain. This is an exceptional opportunity to contribute to key business decisions from a remote location, working with cutting-edge technologies and a talented virtual team.

Key Responsibilities

• Develop and implement sophisticated statistical models and machine learning algorithms to analyze insurance data (e.g., claims, policy, customer behavior).
• Extract, clean, and transform large, complex datasets from various sources.
• Identify key trends, patterns, and insights that can inform pricing, underwriting, fraud detection, and customer engagement strategies.
• Design and conduct A/B tests and other experiments to evaluate the effectiveness of data-driven initiatives.
• Build predictive models for customer churn, risk assessment, and lifetime value.
• Visualize data and communicate complex findings effectively to both technical and non-technical stakeholders.
• Collaborate with actuarial, product development, marketing, and IT teams to integrate data-driven solutions.
• Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence relevant to the insurance industry.
• Contribute to the development and maintenance of data infrastructure and pipelines.
• Ensure data quality and integrity throughout the analytical process.

Requirements

• A Master's or Ph.D. degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.
• A minimum of 4 years of experience as a Data Scientist, with a significant portion focused on the insurance or financial services industry.
• Proficiency in programming languages commonly used in data science, such as Python or R.
• Strong experience with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and SQL.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent understanding of statistical modeling, data mining, and machine learning techniques.
• Ability to work effectively in a fully remote environment, demonstrating strong self-discipline and time management skills.
• Outstanding analytical, problem-solving, and critical thinking capabilities.
• Strong communication and visualization skills, with the ability to present complex data insights clearly.

Benefits

• A competitive annual salary of R.
• Fully remote working arrangement offering maximum flexibility.
• Comprehensive health, dental, and vision insurance coverage.
• Generous retirement savings plan.
• Ample paid time off and public holidays.
• Opportunities for continuous learning and professional development in data science.
• Access to advanced analytical tools and platforms.
• A collaborative and innovative virtual work environment.