Data Scientist I - FSP

Job Description

Who Are You?

A person who can provide data science expertise in the following areas:

• Understanding and effectively working with a wide variety of data sources, with a focus on accelerometry data and wearable devices. The data scientist may work with additional physiological data including with respiration, ECG, EEG voice recordings, video or imaging data, or electronic health records.
• Working with clinicians and researchers to relate study findings to disease biology. Ideally the candidate will have some training in neuroscience or a related field.
• Applying a breadth of data science methodologies as needed for various projects and data types. In particular, this candidate should have significant signal processing skills, ideally including advanced EEG analysis methods that characterize coupling and connectivity across frequencies and brain regions. Projects will also require advanced analytical and statistical methods, such as statistical inference and modern methods for machine learning and AI.
• Identifying and applying state-of-the-art data manipulation and analysis tools, in Python, R or similar languages, to develop bespoke analysis pipelines.
• Independently designing studies, ranging from simple to more complex, and supporting all aspects of projects from data wrangling through to machine learning and statistical analysis.
• Understanding how data science projects fit within client's clinical and preclinical efforts, with the goal of using data science to better understand the patient journey and to help us tailor interventions that maximize patient benefit.

Responsibilities

As a Data Scientist, your responsibilities will include:

• Work closely with client's Quantitative Sciences (QS) staff to support program needs in a timely manner.
• Perform end-to-end data analyses, from hypotheses formulation, experimental design, writing analysis plans, data cleaning, executing analysis, and preparing reports and documentation.
• Strengthen client’s advanced analytics toolkit by identifying and applying emerging techniques, as well as by advancing the state of the art and developing novel analysis tools as needed.
• Collaboration with QS staff and their cross-functional collaborators to understand disease biology and to identify or develop appropriate goals for data science work (for example identifying sensitive and specific endpoints for segmenting patient population, tracking disease progression, quantifying quality of life, etc.)
• Work closely with client's statisticians to ensure statistical issues in data analysis are addressed as needed.
• Anticipate and communicate internal and external resource and quality issues that may impact deliverables or timelines of the program. Propose and implement solutions. Escalate issues to management as appropriate in a timely manner.

Qualifications

Here at Cytel we want our employees to succeed and we enable this success through consistent training, development and support. To be successful in this position you will have:

• Education in a relevant field, for example a) PhD in a field such as Neuroscience, Biostatistics, Physics, Electrical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics with 1-3 years of experience and a clear interest in data science methods, or b) Master’s degree with 3-6 years of relevant experience.
• Expert-level knowledge of data science programming languages (Python and R, or similar) and experience with recommended practices for software development.
• Significant depth of expertise in at least one field relevant to the job (for example, machine learning, signal processing, etc.).
• Ability to work independently on complicated datasets, including all aspects of data analysis (data cleaning, algorithm development, statistical analysis, and documentation).
• Strongly prefer a working knowledge of UNIX operating systems, ideally with experience in high-performance computing environments.
• Excellent oral and written communications skills.
• Strong project management skills.
• Willingness and ability to self-educate in new areas.
• Strong collaborative skills and ability to work with a cross-functional team.