We are seeking a Data Scientist to contribute to our top biotechnology client. The role of a Data Scientist is to work in Research and PreClincial IT organization, develop and apply AI/Client models and analytical algorithms to our scientific and operational data, in order to gain more insight to accelerate drug discovery and development. You will be working with a broad spectrum of datasets, including omics, experimental data for drug target identification and evaluation, lead selection, evaluation, and optimization, as well as operational data supporting the R&D processes. This will require basic scientific knowledge to communicate with bench scientists, understand the questions they are trying to ask of the data, and formulate plans for solution development and delivery. Additionally, you will be situated in a highly matrixed organization, interacting with the Research Data Lake (RDL) team, Scientific Business Analysts, Data Curators, Solution Partners, and the Data and Analytics Enablement team for data modeling, acquisition and manipulation, tool development and platform access and sharing.
The right candidate should be passionate about gaining insight for process improvement and supporting intelligent decision-making by applying algorithms to relevant datasets.
- Be innovative at solution approaches and delivery plans with a "scientific” mindset.
- Knowledge of therapeutic drug discovery and development processes; Understand the data landscape in Research and preclinical Development functions.
- Participate in data acquisition and architect activities such as discovery, storage, curation, transformation, and integration
- Perform exploratory data analysis to define analytical models
- Develop and apply the appropriate data science techniques and libraries to address business challenges/problems
- Develop advanced quantitative models using a variety of programs/software to support predictive, prescriptive, and diagnostic assessments
- Perform multiple forms of advanced analyses, optimization, text mining, Client/AI, and statistical models and techniques
- Develop front-end user interface for data presentation and visualization
- Build, test, validate, and demonstrate analytical models through various relevant error metrics and calibration techniques
- Provide expertise for analytical, programmatic, and operational analysis.
- Document and explain analytics model behavior and outcome
- Deploy models into production
- Partner effectively with internal teams and vendors to coordinate cross-functional analysis and data acquisition.
- Comply with regulatory, security, and privacy requirements as it relates to data assets.
- 5+ years of experience with data exploration, data cleaning, data analysis, data visualization, or data mining
- 5+ years of experience analyzing structured and unstructured data sources
- Experience developing predictive data models, quantitative analyses and visualization of targeted data sources
- Experience with natural language processing, text mining, or machine learning techniques
- Experience using data analysis and/or visualization tools such as Apache Spark, Jupyter, DataIku, Spotfire, Tableau, etc
- Experience with scripting languages for user interface creation
- Experience interacting with scientists, peers, and cross-functional teams to drive a common understanding of data initiative outcomes
- Collaborative, agile mindset to drive speedy, creative, and efficient use of technology and data to drive business value and insight through IT solutions
- Capable of translating and presenting concepts into practical business terms in both small and large group settings
- Experience in business process & requirements gathering in a plus
- Excellent listening skills and strong communication to bench scientists and IT co-workers
- Strong problem-solving skills
- Passion for data, science, discovery, and exploration
- Ability to work independently as well as collaboratively in team settings
- Adaptive and learning agility
Nice to Haves
- Experience working in a pharmaceutical or academic setting
- Track record of delivering impactful data science solutions to solve real-world problems
- Broad knowledge in data architect & management, data wrangling, ontology
- Experience with Machine Learning, Artificial Intelligence, Natural Language Processing (NLP)