Why is this job for you?
We are focused on discovering new patterns in big data. These pattern discoveries will significantly and positively impact people lives. Our initial work is in the biomedical space, focusing on identifying the patterns related to breast cancer, lung cancer, and other diseases such as Chron’s disease. This job is for you because we are taking on what has been viewed as an intractable problem. We learn daily from each other in the space of mathematics, machine learning, data science, bioinformatics and biology, with each of our are experts working at or beyond the state of the art. Learning, sharing ideas, and synthesizing information is our passion. Making a positive impact by combining leading-edge research with emerging technologies is our mission. That’s why we are here. We’ll take on additional domains such as finance, transportation, energy, etc. as time and resources allow.
You are well suited for this job because you have experience in mathematics spanning many areas. You have done work in the areas of decision trees and understanding partitioning and/or clustering of data in large data sets. You are familiar with topological data analysis techniques and have good intuition when working with high dimensional data sets. You know dimensional reduction strategies and the associated tradeoffs and remedies of the various techniques. Most importantly, you like interesting challenges in applied mathematics and enjoy doing research on best techniques. You enjoy working with data sets to understand the nature of both the algorithms and the datasets; how tuning of algorithms and/or hyperparameters can positively influence the results while retaining data integrity. An ideal candidate would have the following traits in the realm of mathematics: passion, resourcefulness, and intuition.
- Leverage existing work which reduces relationships in high-dimensional, complex data sets to lower dimensions.
- Design and develop algorithms to solve data analysis challenges. Introduce and apply novel mathematics techniques for partitioning data spaces, clustering data, and implementing topological data analysis (TDA).
- Provide guidance on staging or coupling various applied mathematics techniques, such as TDA, balancing effectiveness with time-to-market.
- Learn new approaches, work collaboratively, and share expertise freely on data insights, algorithms, and novel strategies.
- Suggest proof-of-concepts that can be implemented with our data sets and specifying expected outcomes, resources, and estimated timelines for the implementation.
- Build prototypes for specific algorithm chains in C/C++, python and/or various packages such as scikit-learn.
- PhD in Applied Mathematics or a MSc with equivalent experience.
- Deep knowledge of mathematics related to decision trees, partitioning data spaces, topological data analysis (TDA) and clustering strategies.
- Able to think outside traditional algorithms; translating and applying concepts from one domain to other domains.
- Comfortable working with high-dimensional, complex data. Has experience with multiple dimensional reduction techniques.
- Able to share knowledge with the team. Effective communicator.
- Able to program in in python, C/C++, or similar languages.
- 15 years’ work in one of the following fields: advanced data science, applied mathematics, TDA.
- Experience working with high-dimensional, sparse data sets.
- Knowledge and practical experience with machine learning techniques with the ability to perform comparative analysis of the various techniques as applied to different problem spaces.
- Experience working with statistical analysis tools such as R, MATLAB, SPSS or SAS.
- Ideal candidate will have successful experience as a professor of mathematics.
This position reports to our Head of Data Science
Located in Redmond, Washington
Travel is minimal, less than 25%
Is this right for you? Send us an e-mail at email@example.com
Pattern Computer is an equal-opportunity employer