Data Scientist

Verikai stands apart from traditional insurtech companies. As a remote-first team, we're fueled by a commitment to cultivating top talent. Here, you'll thrive in a collaborative environment that celebrates integrity, teamwork, and inclusivity. Diverse perspectives are valued, and a "dare to fail" spirit fuels groundbreaking innovation.

This dedication to fostering talent is central to our mission. We're revolutionizing the insurance industry through cutting-edge technology, and we're looking for passionate individuals to join us on that journey.

Verikai is the leading provider of predictive analytics and AI-powered solutions for the insurance industry. Through our innovative platform, Verikai empowers insurers with advanced data-driven risk assessment insights, streamlining the underwriting process and optimizing business outcomes. With a commitment to technological advancement, Verikai is changing the insurance industry by assisting underwriters with decision-making when it comes to risk.

We are a growing and well-funded company with a great product and even better ideas. If you want to make an immediate impact on the way the insurance industry works while working in a fun, fast-paced, and supportive environment, you’ve come to the right place.

As part of the analytics team at Verikai, you will be in front of real customer issues and the data they generate in real time. You will be tasked with analyzing large-scale datasets and rewarded by witnessing your analysis been leveraged by the customers and creating tremendous value for them. You will have the opportunity to train yourself, with help from more senior team members, on using various data tools to analyze various types of complex datasets. You will also be able to manipulate our cutting-edge machine learning platform and improve it to build insightful models while learning and practicing how to build a truly operational model. Our culture will allow you to work closely with all aspects of the business, and really shine on building up our analytics process and infrastructure.

Responsibilities

• Innovate and implement cutting-edge machine learning algorithms, aiming to extract greater lift from our data and deliver enhanced value to our customers
• Proactively seek out and identify useful attributes from various data sources to enhance our core data assets. Rigorously validate the utility and relevance of new data to ensure it contributes to the improvement of our models and insights
• Conduct thorough descriptive and statistical analyses on customer data to uncover valuable patterns and insights. Apply creative analytical approaches to ensure that results are directly aligned with customer needs and support their business decision-making processes
• Present results, findings, and models to customers and stakeholders with a high level of technical expertise and industry knowledge. Act as a technical expert, industry insider, and company promoter, ensuing that presentations are clear, informative, and persuasive
• Work closely with other data scientists, engineers, product managers, and other stakeholders to integrate machine learning models and statistical analyses into our products and services. Ensure seamless collaboration and knowledge sharing across the teams
• Keep up with the latest developments and trends in machine learning, data science, and the insurance technology industry. Apply this knowledge to continuously improve our models, methodologies, and approaches
• Adhere to data privacy regulations and ensure that all data handling practices comply with relevant legal and ethical standards. Maintain the highest levels of data security and confidentiality

Skills and Qualifications

• Bachelor’s degree or above in Statistics, Mathematics, Actuarial Science or Computer Science with at least 2 years of relevant working experience
• Possesses extensive expertise in machine learning algorithms and techniques, including supervised learning, unsupervised learning, and deep learning
• Has in-depth knowledge of statistical analysis methods and their applications in data science
• Highly proficient in Python and machine learning frameworks, with extensive experience in writing efficient, maintainable, and well-documented code
• Has a working knowledge of PySpark, capable of performing basic data manipulation and processing tasks in a distributed computing environment
• Basic understanding of SQL and experience writing queries to extract data
• Experienced in optimizing data workflows for efficient large-scale data processing and analysis
• Experience of working on a cloud-based ML platform is a plus; Experience of working with insurance related data is a plus
• Takes full accountability and ownership for their work, ensuing tasks are completed to the highest standards and within deadlines
• Demonstrates exceptional attention to detail in all aspects of work, ensuring accuracy and completeness
• Able to think critically and make informed decisions by assessing all available data and considering various perspectives
• Maintains a professional, positive attitude with reliability, flexibility, and a strong work ethic
• Committed to supporting and assisting colleagues, contributing to a collaborative and team-oriented work environment
• Communicates clearly and effectively, both verbally and in writing, ensuing complex statistical concept is conveyed accurately to colleagues and stakeholders

Security, Confidentiality, and Availability

• Review, accept, and adhere to all security and confidentiality policies and procedures listed below where many policies apply directly to every company employee and some policies only apply directly to employees in particular departments:
  • Proprietary Information and Inventions Agreement (PIIA)
  • Acceptable Use Policy
  • Access Control and Termination Policy
  • Business Continuity and Disaster Recovery Plan
  • Change Management Policy
  • Code of Conduct
  • Configuration and Asset Management Policy
  • Data Classification Policy
  • Data Retention and Disposal Policy
  • Encryption and Key Management Policy
  • Information Security Policy
• Make conscientious decisions in what information is shared with internal and external stakeholders keeping in mind security and confidentiality policies
• Be available during local regular business hours and respond to requests and concerns as quickly as possible outside of those hours based on urgency

Reports to: Data Science Lead

Salary Range: $110,000 to $140,000

Company:

Salary Range:

Benefits:

Compensation varies by role, position level, and location. Individual pay is influenced by skills, education, training, certifications, experience, and the role's scope and complexity, along with business needs.

We offer a competitive Total Rewards package, including medical, dental, and vision plans starting on day one, PTO, paid holidays, commuter benefits, an employee stock purchase plan, education reimbursement, paid parental leave/adoption assistance, and a 401(k) plan with company match. These benefits are available to eligible full-time and part-time employees.

Your recruiter can provide more details about our total rewards and specific compensation ranges during the hiring process.