Ascend is a life science product company operating at the intersection of data, digital, and research. In partnership with the Greater Dayton Area Hospital Association (GDAHA) we are owned, in-part, by three major healthcare networks with access to 29 hospitals and healthcare organizations. With our growing client base and continued passion for technology, we are seeking candidates who share our passion and have an interest in creating advancements in the health and life sciences industry.
A key vertical of Ascend is data science. We find creative ways to integrate our capabilities with hospital data, operations, and workflows, as well as identify community or industry opportunities. Hospitals use our services to improve quality, optimize operations, and reduce costs. Meanwhile, community and industry clients rely on us to transform healthcare data into insights and analytic products such as interactive reports, dynamic dashboards, and machine learning algorithms.
Our clients include exciting companies such as Oculus VR, Kettering Health, Midmark, Verily Life Sciences (Alphabet’s healthcare organization), the Greater Dayton Area Hospital Association, and many more.
The core function of the Data Scientist is to frame a real-world problem as a standard data science task. This position is primarily responsible for contributing to, and possibly managing, data science/analysis projects that use various data sources, such as raw healthcare data to customer-specific data, ideally following the CRISP-DM open standard. This position will also use systems thinking and methodologies when considering how models and analytic capabilities will integrate in Ascend’s product development process and ensure that solutions align with the company’s key strategic initiatives, as well as the needs of its partners and clients.
Specific focus areas will include data manipulation, data mining, and algorithm development using techniques such as clustering, anomaly detection, association-rule mining, and prediction (i.e. classification, regression, etc.). Responsibilities will also include contributing, and possibly managing, project efforts throughout their lifecycle, including providing end deliverables such as technical reports and presentations. The Data Scientist is also expected to contribute to strategy and discovery work, including effectively communicating with key stakeholders and leadership.
PRINCIPAL DUTIES & RESPONSIBILITIES
Problem Understanding & Client Engagement
- Interface with hospitals, community partners, and other partners/clients to identify challenges or opportunities that align with key strategic healthcare initiatives
- Foster new business growth by gaining intimate understanding of client needs and proposing new solutions
- Contribute to, and possibly manage, projects to ensure that all deliverables are met
Data Preparation & Analytics
- Clean, restructure, and manipulate data into a useable format for analysis
- Employ data mining techniques to identify influential variables and extract actionable insights
- Perform feature engineering for machine learning, as applicable
- Design, prototype, and refine production ready, predictive algorithms or models
- Work with digital team to transform static insights into dynamic reports or other digital products
- Work directly with data architects, software developers, and product managers to seamlessly integrate products with hospital network operations and workflows
- Translate analytical findings into reports, publications, presentations, or other forms of communication
- Engage with clients and partners to communicate findings and identify follow-on opportunities
This job description is not intended to be all inclusive and the employee will also perform other reasonably related business duties as assigned by the immediate supervisor and other management as required.
- Bachelor’s degree or above in quantitative discipline (e.g. operations research, statistics, bioinformatics, mathematics, computer science, industrial engineering, or other related fields)
- 2+ years of relevant experience in data science, analytics, or another related STEM field
- Prior experience in healthcare is desired but not required
- Open source programming languages (Python, R, etc.)
- Data science related packages such as NumPy, pandas, scikit-learn, ggplot2, Tidyverse, Shiny, Caret, etc.
- Demonstrated ability in selecting suitable statistical techniques for a given dataset
- Expertise in machine learning techniques including regression models, GLM, SVM, neural networks, tree-based models (e.g., Boosting, Decision Trees, Random Forests)
- Experience with deep learning frameworks such as Tensorflow, Keras, PyTorch, etc.
- Database experience (SQL, MongoDB, etc.)
- Ability to translate analytic results into intuitive insight and recommendations
- Demonstrated leadership and self-direction. Willingness to collaborate and learn new technical skills/techniques
- Natural language processing (NLP) or mathematical programming (optimization) is desired but not required
BENEFITS & PERKS
- Wellness benefits – Comprehensive health care options, 401k plan and employer matching, life insurance
- Work-Life balance – Generous vacation policy, parental leave
- Personal Growth – Personal development budget and professional management
Tools and Equipment Provided
- 13 or 15inch Macbook Pro, or comparable Windows device
- 27in 4k monitor, laptop stand, keyboard, mouse and the tools you find necessary to get your job done
- Slack, Office 365 Suite and the modern tools you need to get your job done
- Light or local travel — up to 5%
Physical & Mental Demands
- Frequently required to sit at a desk/workstation for long periods of time
- Ability to effectively communicate to employees/clients via phone, computer or in-person
- Moderate lifting and carrying of supplies, files, etc.
- Body motor skills sufficient to enable the incumbent to move around the office environment
- Ability to analyze unique situations and develop an appropriate response
- Work typically performed in an office setting.