DawaSwift is the leading mobile technology and data science company that delivers medicine from local pharmacies to patients' homes through a tight network of local drivers/riders and also gives small medical loans to patients on its mobile app. With headquarters on the internet and office presence in Toronto and Montreal (Canada) and Nairobi (Kenya), DawaSwift is creating the world's widest network of local pharmacies to serve local patients through an AI powered web platform that also connects them with local drivers to facilitate deliveries of medical products in real-time.
Leverage a unique, diverse, and deep data set to find connections across these data sources. Communicate findings to the team and integrate them into models.
Own the full-cycle of a model from ideation and training through deployment into our production environment. This might be a credit model, fraud model, marketing model, or an iteration of an existing model.
Monitor model performance once deployed and iterate rapidly if necessary.
Contribute and share your findings and knowledge of data science and other modeling with all appropriate cross-functional teams.
Partner with the Engineering team to develop, test and deploy models.
Pull data from MySQL or other data stores, handling all the ETL from the DB to running the model to obtaining a decision.
4+ years of experience in a data science role.
Masters or PhD in a quantitative field.
Fluent in Python and packages related to machine learning.
Experience with deploying data science models in a production environment.
Preferred Skills & Experience:
Experience in building fraud, credit, or risk models
Expertise in NLP, network analysis, or geospatial analysis
A Successful Candidate is (a/an):
Problem Solver: You thrive on finding novel solutions to hard problems. These problems may have ranged from extracting a new dataset from an unexpected source, to building cohorts for customer retention analysis, or the NY Times Saturday crossword.
Communicator and Listener: You thrive on finding novel solutions to hard problems. These problems may have ranged from extracting a new dataset from an unexpected source, to building cohorts for customer retention analysis, or the NY Times Saturday crossword.You know your stuff is complicated, but can you communicate complex ideas to others in a manner that is easily understood and digestible? Can you collaborate well with your peers in growth/portfolio/customer experience? There is a large research component to the job, and this research needs to be effectively shared with the rest of the company.
Independent Learner: We encounter new problems that aren’t in textbooks. You have the ability to learn on your own about new concepts and techniques.
Curious: You aren’t content until you understand why the features you have built have the explanatory power they do, and why they aren’t just a spurious correlation.
Opinionated (but Open-Minded): We are looking for someone to add diversity of thought to our current ensemble of data scientists.
Teammate/Partner: Trust in your team and putting the team and mission above individual highlights (with an understanding that the collection of individual highlights and performance makes the team work).