Senior Data Scientist @ Sapiens

We are looking for an enthusiastic Data Scientist with a foundational understanding of data science principles and an interest in the insurance industry. The role involves working alongside senior data scientists to analyze data, build models, and generate insights.

What youll do:

Data Collection & Preprocessing

• Assist in gathering, cleaning, and preprocessing data from various sources, ensuring data quality and consistency.
• Conduct exploratory data analysis (EDA) to identify trends, patterns, and insights within the data.

Model Development & Evaluation

• Building predictive models to enhance accuracy.
• Test and evaluate basic machine learning models, including linear and logistic regression, decision trees, and clustering algorithms.

Reporting & Visualization

• Create clear and informative data visualizations and reports to communicate insights to business stakeholders.
• Tracking key metrics and performance indicators related to business objectives.

Cross-functional Collaboration

• Collaborate with business and technical teams to understand project requirements and contribute to the design of data-driven solutions.
• Participate in team meetings, brainstorming sessions, and discussions on data science projects and initiatives.

Research & Learning

• Stay updated on the latest trends and tools in data science, machine learning, and the insurance industry.
• Participate in ongoing training and development programs to enhance technical skills and industry knowledge.

What to Have for this position.

Must have Skills.

• Education: Bachelors degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. A Masters degree is a plus.
• Experience : 4+ years of experience in data science or analytics
• Basic Industry Knowledge: General understanding of insurance concepts (e.g., policies, claims, risk, customer lifecycle) is desirable but not required.

• Insurance Data Familiarity: Some experience working with structured data (e.g., customer demographics, policy details) and an eagerness to learn about the specific types of data used in the insurance industry.
• Predictive Models: Exposure to basic predictive modeling techniques such as regression, classification, forecasting or clustering. Experience with insurance-specific models (e.g., claims prediction, risk assessment) is a plus.
• Data Preparation: Knowledge of data cleaning and preprocessing techniques, with experience in handling datasets to prepare them for analysis.

• Programming Skills: Proficiency in Python for data analysis, with familiarity in using libraries such as Pandas, NumPy, and Scikit-learn.
• Data Manipulation: Basic skills in SQL for querying and extracting data from databases.
• Statistical Knowledge: Understanding of fundamental statistical concepts, including distributions, probability, hypothesis testing, and descriptive statistics.

Required Soft Skills:

• Curiosity & Willingness to Learn: Enthusiastic about learning new concepts, techniques, and industry-specific knowledge in the insurance domain.
• Problem-Solving Skills: Ability to approach challenges analytically and think critically about data and project requirements.
• Attention to Detail: Keen eye for detail in data handling and model development to ensure high-quality outcomes.
• Communication Skills: Clear and concise communication skills, with the ability to present findings and insights effectively.

Team Collaboration: Willingness to work collaboratively within a team, receiving and applying feedback from senior team members.