Software Development role at GDIT requiring a TS/SCI clearance with Polygraph. Engaging in government projects for software innovation and development in Virginia.
DS
Onsite Senior Real World Data Scientist, Epidemiologist, Biostatistician
Posted 3 weeks ago
About the role
- Senior Real World Data Scientist providing statistical and epidemiological expertise in nutrition and health research. Analyzing large scale observational data and guiding project teams in statistical methodologies.
Responsibilities
- Provide statistical and epidemiological expertise on observational nutrition data.
- Analyze large cohort datasets, surveys, biobanks, digital biomarkers, consortium data and real-world data to generate insights for better nutrition, healthy ageing and prevention.
- Apply advanced techniques such as causal inference to address complex questions in nutrition and health.
- Support our multidisciplinary project teams in Human Nutrition and Care with your statistical know-how.
- Optimize decision-making in all discovery and development phases of our nutrition and care products by designing robust experiments and analyzing data from clinical trials or consumer studies.
- Integrate and analyze data from diverse sources (e.g. combining evidence from observational studies and randomized trials) to perform meta-analyses and develop a comprehensive evidence base for product development and marketing claims in nutrition and care.
- Collaborate closely with bioinformaticians in the team who analyze related omics data.
- Optimize study design for human clinical studies or observational studies in collaboration with study directors and scientists, ensuring scientifically sound and statistically powered designs that can lead to robust results and actionable insights.
- Work closely and in a result-oriented manner with colleagues across disciplines – bioinformaticians, study directors, nutritionists, project managers, data managers, marketing teams, etc. – either as a core project team member or as an ad-hoc statistical consultant, to ensure data-driven decision making.
- Participate in external collaborations on a global scale (with universities, research institutes, industry partners, CROs, etc.) to stay at the forefront of nutritional research and statistical methodologies and to drive innovation in how we use data in nutrition and personal care research, e.g. regarding causal inference and target trial emulation.
- Oversee the outsourcing of data analyses to external partners and ensure that all analyses meet our quality standards and adhere to relevant guidelines and regulations.
- Work on a broad variety of projects and questions and handle competing priorities in a dynamic environment.
Requirements
- A Master’s or preferably PhD degree in Epidemiology, Biostatistics, Data Science, or a related field, with several years of work experience (a PhD will be considered as work experience).
- Solid programming experience in R is essential; experience with programming in Python and ability to read SAS code would be a plus.
- Familiarity with large-scale cohort data and the challenges of working with real-world evidence (e.g. handling biases, missing data, etc.).
- Experience analyzing data from sources like national health surveys or biobanks or nutritional data is preferred.
- Sound knowledge of standard statistical methods, particularly regression and its extensions (e.g. GLMM), as well as experience with causal inference techniques and meta-analysis methods.
- Experience with target trial emulation is a plus.
- Experience with machine learning, advanced analytics, data engineering/wrangling, database tools (SQL), cloud computing platforms (such as AWS), or version control (Git) is a plus.
- Experience with clinical trial data standards (e.g. CDISC) and knowledge of data privacy regulations (e.g. GDPR) is a plus.
- Strong stakeholder management skills – you take initiative, are curious about the goals and context of projects, and can effectively act as a quantitative advisor for both technical and non-technical stakeholders.
- A team player with the ability to communicate complex statistical concepts in a clear and effective way to non-statisticians (e.g. nutritionists, innovation project managers, marketing colleagues).
- You thrive in an open, global, collaborative and diverse research environment.
- A pragmatic and curious mindset with an eye for the big picture – you enjoy identifying gaps and opportunities in large nutritional data sets, validating the evidence, and translating the findings into actionable insights.
- Fluent in English (our business language).
Benefits
- A broad variety of projects, data types, and statistical approaches, ensuring you never stop learning and can apply a wide range of methods.
- A team of diverse, open-minded colleagues who aren’t afraid to think outside the box and challenge the status quo.
- A truly global and collaborative team environment that cares about our employees’ experience and growth.
- The encouragement and support you need to develop professionally and achieve your goals.
- A caring and supportive workplace where you’re empowered to grow, share your ideas, and make a real impact.
- A safe, inclusive workplace where you feel welcome and respected.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Coordenador de Ciência de Dados leading the data team in developing analytical solutions for Caixa Vida e Previdência. Focused on data science and project coordination in a collaborative environment.
Lead and deliver AI initiatives focusing on traditional machine learning and generative AI for Mashreq Bank. Build, scale, and productionize models for business transformation and operational efficiency.
Data Scientist designing and implementing analytical solutions using Python and AI technologies. Collaborating cross - functionally to deliver Generative AI solutions for business needs in a hybrid setup.
Data Scientist developing predictive models and automation workflows for the mortgage lifecycle. Collaborating with cross - functional teams to enhance operational efficiency and customer outcomes.
Data Scientist developing machine learning models and analytics solutions to improve decisions in the mortgage lifecycle from acquisition to servicing. Collaborating with teams on predictive modeling and automation workflows.
Senior Manager in Data Science and Analytics leading statistical modeling for mortgage and consumer lending. Collaborating with teams to deliver data - driven insights and improve operational efficiency.
AR
Internship for AI in document processing at ArianeGroup, focusing on natural language processing and data analysis tasks in a collaborative environment.
Senior Data Scientist focused on Generative AI and LLM at Manulife. Develop and implement machine learning models to solve business problems and mentor peers.
Data Scientist specializing in AI and LLM technologies at F5, innovating security platforms through AI/ML development and collaboration.