Senior Data Scientist
American Red Cross
We roll up our sleeves and donate time, money and blood. We learn or teach life-saving skills so our communities can be better prepared when the need arises. We do this every day because the Red Cross is needed - every day.
General overview of the role
By joining the American Red Cross you will touch millions of lives every year and experience the greatness of the human spirit at its best. Are you ready to be part of the world’s largest humanitarian network?
The American Red Cross is looking for a seasoned Sr Data Scientist to leverage existing data to develop & execute predictive models and advanced analytics to help solve complex business problems. The Sr Data Scientist will use advanced techniques that integrate traditional and non-traditional datasets to enable analytical solutions. This person will also apply predictive analytics, machine learning, and optimization techniques to generate management insights and optimize business functions.
We are seeking candidates with a depth of knowledge in statistics, as well as hands-on experience building a range of predictive models using artificial intelligence and machine learning.
This position will work virtually from a home/office anywhere in the USA.
Utilize advanced statistical techniques to create high performing predictive models and creative analyses to address business objectives and client needs. Tests new statistical analysis methods, software and data sources for continual improvement of quantitative solutions.
Work with Business SMEs to create models which predict the outcome of key business processes
Lead and contribute to data analysis and modeling projects from project or prototype design
Gathering and analyzing data, identifying key prediction/classification problems, devising solutions and building prototypes.
Follow industry trends in related data analytics processes and businesses.
Develop high-performance algorithms for predictive analytics. Testing and implementing these algorithms in scalable, product-ready code.
Ideal candidate will possess a PhD with at least 3+ years of data science expertise; However candidates with equivalent and relevant years of experience in lieu of Post graduate Degree will be reviewed
Advanced applied statistics skills, such as distributions, statistical testing, regression, etc.
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
Strong algorithmic problem solving and software development skills (R, Python, or similar)
Demonstrated capability to develop proof-of-concept prototypes for experimenting with novel algorithms
Demonstrated experience and accomplishments in the use of data mining, machine learning, and predictive analytics to address real-life problems.
Past experience in analyzing large scale data and distributed algorithms
Excellent analytical, communication (both verbal and written), interpersonal, and organizational skills.
Must be able to communicate effectively and clearly present technical approaches and findings.