Foundation

About Early Signal (EaSi): We are a new non-profit developing a smart informatics analytical system designed to handle wearable device data capturing motor, cognitive and other functional outcomes to assess brain disease onset, progression and recovery. EaSi platform will handle unstructured wearable device data, focusing on continuous passive acquisition, and will provide analytical tools designed to provide maximal sensitivity to idiosyncratic individual health trajectories. EaSi focuses on health analytics for rare disorders and for the underserved population.


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Senior Director Data Science​


Duties
. The successful candidate will design, develop, optimize, and maintain algorithms to import, clean, impute, transform, and model data. The successful candidate will oversee the work of data scientists, analysts, informaticians and junior software developers. The successful candidate will monitor progression for projects, ensure timely delivery of milestones, and enforce quality control. The successful candidate duties may include designing, developing, or overseeing such work, relational databases and necessary GUIs. Importantly, the successful candidate will identify and hire the data scientists that will form the core of the foundation.

Expertise. Background in technology, management, relational database design and machine learning. Good knowledge of statistics, probability theory, time series analysis, and predictive modeling (multiple regression technics, decision trees, cluster analysis, ensemble classifiers). Experience handling big data and working with AWS.  Knowledge of R and python’s numerical and statistical packages (Pandas, Numpy, SciPy, scikit-learn). Ability to design large scale data pipelines to acquire and handle unstructured noisy data prior to fitting models. Knowledge of complex database queries using distributed computing frameworks (MapReduce, Hadoop, Scala, Spark).

A big plus will be demonstrable experience in: Topological data analysis, network analysis, deep learning and anomaly detection. Experience in designing scalable information technology and ETL platforms.

Qualifications. Ph.D in Bioinformatics, Mathematics, Physics, relevant computational discipline, or advanced degree in Computer Science.

The ideal successful candidate will possess the following experience: A minimum of 10 years of work experience in: health analytics, biostatistics, mathematics, economics, wearable technology, telehealth, or relevant discipline.
Ability to work in a team with scientists of differing experience to come up with smart solutions for complex statistical modeling projects. Publications in peer reviewed journals and invited conference presentations. Experience working with large data sets including cleaning, transforming, merging and/or managing data. Experience in using various technologies to solve unique challenges while developing new approaches for data analysis to identify answers that could change lives. Love of data modeling. Passionate about using cutting edge technology to solve unique problems, developing new approaches, combing the data to find the answers that could change lives.Track record showing experience mentoring and guiding team members of varying experience levels through data science.


Benefits. We provide generous health insurance and 401K matching.


Location. New York City.


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Data Scientist

Duties. The successful candidate will design, develop, optimize, and maintain algorithms to import, clean, impute, transform, and model data. The successful candidate will work with project managers to transparently monitor progression for projects, ensure timely delivery of milestones, and enforce quality control. The successful candidate duties may include designing, and/or developing such work, relational databases and necessary GUIs.

Expertise. Background in wearable technology, modeling and machine learning. Good knowledge of statistics, probability theory, time series analysis, and predictive modeling (multiple regression technics, decision trees, cluster analysis, ensemble classifiers). Experience handling big data and working with AWS.  Knowledge of R and python’s numerical and statistical packages (Pandas, Numpy, SciPy, scikit-learn). Ability to design large scale data pipelines to acquire and handle unstructured noisy data prior to fitting models.

Qualifications. Ph.D or MS in Bioinformatics, Mathematics, Physics, or Computer Science.

Experience: 
A minimum of 3 years of work experience in health analytics, biostatistics, mathematics, economics, wearable technology, telehealth, or relevant discipline.


A big plus will be demonstrable experience in: Topological data analysis, network analysis, deep learning and anomaly detection. Experience in designing scalable information technology and ETL platforms. Knowledge of complex database queries using distributed computing frameworks (MapReduce, Hadoop, Scala, Spark). 


Other experience: Ability to work in a team with scientists of differing experience to come up with smart solutions for complex statistical modeling projects. Publications in peer reviewed journals.  Experience working with large data sets including cleaning, transforming, merging and/or managing data. Love of data modeling. Passionate about using cutting edge technology to solve unique problems, developing new approaches, combing the data to find the answers that could change lives.


Location: New York City


Benefits: Generous health and 401K benefits.