Data science internship

Safe-esteem is a Miami-based technology startup focused on improving personal risk measurement, communication, and decision-making. We use big data, analytics, human and Artificial Intelligence (AI) along with cognitive and behavioral science to develop consumer and commercial applications. We recently released Safe-xplore – the most advanced personal and travel risk rating platform on the market today, and Safe-xplore Personal Edition – a free, public-interest Web and mobile app designed to help people make smarter risk & safety decisions at home or when traveling.

We are looking for data science & engineering students and professionals to help with a multitude of data science projects and tasks - including data collection, processing, analysis, AI/ML applications, etc.. This is an internship opportunity aimed at offering hands-on experience with a recognized risk mitigation SMEs team and a high-impact startup.

Time commitment may range between ten and 20 hours/week, over two to four months. Through this internship, we hope to identify highly motivated and competent candidates to join our team in a formal/permanent role.

Our work and products focus on the domains of individual risk, including criminal victimization, safety and transportation, health and disease, etc. We are constantly exploring, ingesting, and analyzing data sets in these domains to produce new insights, find patterns and trends, effectively communicate/present data to our team and customers, and develop our proprietary algorithms.

• The data you'll be working with will include, but not be limited to: Centers for Disease Control (CDC), the FBI’s National Incident-Based Reporting System (NIBRS), National Crime Victimization Survey (NCVS), Global Health Data Exchange (GHDx), the American Community Survey, the World Health Organization (WHO), plus other national, local, and proprietary sources.

• The work you'll be expected to perform may include:

  • Collect raw data collection (e.g., scraping, APIs )

  • Perform basic data engineering/ETL (e.g., data cleaning, transformation, and database design)

  • Develop interactive visualizations (using open source libraries, Power BI, or Tableau)

  • Apply machine learning and parametric statistical modeling (primarily risk models)

  • Work with our software engineers to improve the user interface and data representation so as to better execute our core algorithms

  • Assist with formulating extensions to the core algorithm and improving imputation techniques

  • Prototype and present solutions to company leadership

• Our ideal candidate will have the following skills/competencies:

• Fluent in English

• Engineering, Statistics, Data Science, Applied Mathematics, Computer Science, Physics, Computational Biology, Computational Chemistry or related quantitative field

• Advanced statistics & probability knowledge, particularly in the areas of health & disease and/or actuarial modeling

• Familiarity with predictive modeling and analysis of large datasets

• Solid R and/or Python programing ability -- ability to develop and debug analytical scripts with minimal guidance and supervision

• Experience with Bayesian modeling tools (e.g., AgenaRisk, Analytica, etc.) is a plus

• Knowledge of geospatial analysis and geostatistical models (e.g., gaussian processes a.k.a. kriging) is a big plus

If interested, please send us your resume to info[at]safe-esteem.com