Data Scientist Responsibilities
Predictive analytics using big genetic, clinical, biographical and laboratory results data
Assist in bioinformatics analysis
Work with stakeholders to identify opportunities for leveraging clinical and genetic data to identify patterns and trends and optimize clinical decisioning.
Continuously evaluate the accuracy and utility of new data sources and data gathering methods.
Develop custom data models and algorithms to apply to data sets.
Use predictive modeling to increase and optimize clinical decisioning, identify possible health red flags, and develop diagnostic aids.
Develop the KIBs A/B testing framework and test model quality.
Coordinate with different functional teams to implement models and monitor outcomes.
Lead the development of tools and processeses for the monitoring and analysis of data accuracy and model performance.
Qualification Requirements
We’re looking for someone with 3-5 years of experience manipulating data sets and building statistical models, has a bachelors degree in the biomedical / biological sciences with advanced qualifications or sound knowledge in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
Proficiency in programming and experience with several languages: Perl, C, C++, Java, PHP, JavaScript, etc.
Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
Experience querying databases and using statistical computer languages: R, Python, MYSQL, etc.
Experience using web services: AWS, S3, Spark, DigitalOcean, etc.
Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
Experience visualizing/presenting data for stakeholders using: R, Periscope, Business Objects, D3, ggplot, etc.
The ideal candidate should also have the following attributes:
Ability to work independently and solve problems
Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
Experience working with and creating data architectures.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Excellent written and verbal communication skills for coordinating across teams.
A drive to learn and master new technologies and techniques.
How to Apply
Applications should be addressed to The Human Resource Officer, Bioinformatics Institute of Kenya, [email protected] so as to reach her not later than 18th Augutst, 2022