Data Scientist
New York City, United States
Afficiency
Afficiency - an insurtech transforming the life insurance buying process for your clients. Instant underwriting. 100% digital. No medical exam.About Afficiency
Afficiency was founded with the goal of providing life insurance to everyone on the platforms they already trust. We’ve launched with enormous success and are growing fast.
Afficiency has developed a digital life insurance platform that allows new products to be digitized and made available for distribution rapidly, completely via API. Headquartered in New York, the company has been partnering with insurance carriers and reinsurers since 2018 to bring new innovative products to market. All of Afficiency’s life insurance products are completely digital, provide instant coverage and are accessible via the many platforms with whom we partner. Simply put, there is nothing comparable to this in the marketplace.
Afficiency is comprised of proven start-up entrepreneurs and life insurance innovators. We have a growing team and are excited about changing a $600B industry. We are making life insurance accessible to millions of people who would otherwise not have access to these important products that protect their families. Learn more at afficiency.com
About the Role
Please note that this job is only hiring candidates that live in the Metro NYC area and are able to commute to the office.
We are seeking a data scientist to join our business intelligence team to help us make better business decisions based on our data. The ideal candidate will have a working knowledge of statistics, mathematics, and data science programming languages (e.g., SQL, R, Python).
Your primary responsibilities will be performing statistical analyses and identifying patterns and trends that can improve our products’ and services’ efficiency and usability. You will also be expected to maintain and improve our data infrastructure and tools.
Responsibilities
- Work with stakeholders to identify key metrics and opportunities for improving business processes, products, and services
- Build, deploy, and maintain data management systems and back-end data infrastructure for our business intelligence pipeline
- Perform data mining, exploration, and analysis
- Create data visualizations, reports, dashboards, and data audits
- Design, train, and implement machine learning algorithms
- Leverage predictive models to optimize customer experiences
- Creating automated anomaly detection
Requirements
- Bachelor's degree in data science, data analytics, or related field
- Master’s degree or Ph.D. in a quantitative field, such as statistics, computer science, mathematics, or engineering
- Proficiency in Python, Java, or Kotlin
- Knowledge of data science toolkits such as R, NumPy, and MatLab
- Experience with big data analytics technologies such as Spark and Hadoop
- Experience with data visualization tools such as D3.js and Tableau
- Expertise in data mining and machine learning
- Working knowledge of statistical models and business intelligence
- Familiarity with cloud-based infrastructure
- Ability to store and process unstructured data with NoSQL databases and machine learning models
Benefits
- Competitive package with benefits and equity
- Flexible vacation and working from home (continuing post-pandemic)
- Work at a supportive and fast-growing start-up with a fantastic team
- Opportunity to make an impact in the lives of tens of millions of consumers
- Environment to learn from other team members, grow a business from the ground up and quickly assume additional responsibility
- Support in developing your skills and accelerating your career quickly
- Regular team get-togethers in awesome locations
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Big Data Business Intelligence Computer Science D3 Data Analytics Data management Data Mining Data visualization Engineering Hadoop Machine Learning Mathematics Matlab ML models NoSQL NumPy Python R Spark SQL Statistics Tableau Unstructured data
Perks/benefits: Career development Equity Flex hours Flex vacation Startup environment
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