Axiom has a long-term contract for a Data Scientist with one of our clients.
The Data Scientist will translate business needs into analytic questions; design and conduct rigorous analyses of clinical, financial, customer, and operational data; and translate these analytic findings into predictive models and evaluation results for our business partners.
- Consult with key internal and external stakeholders to determine how best to leverage predictive modeling and advanced analytic methods to support business objectives across client.
- Ability to select appropriate modeling approaches for a given analytic problem (regressions, time series analysis, neural networks, decision trees, ensemble models).
- Implement the models in a variety of modeling tools, achieving highly accurate models.
- Understand the underlying statistical concepts and computational approaches that enable efficient execution of models and may be able to design and implement modifications and enhancements to the computations.
- Develop sound analytic plans based on available data sources, business partner needs, and required timelines.
- Apply innovative approaches to understand and predict what will happen across the business.
- Manage deliverables across multiple projects in a deadline-driven environment and project related to a wide variety of business settings and clinical needs.
- Present analytic findings in a variety of formats (reports, PPT, graphs, figures and tables), formulating recommendations, and effectively presenting the results to non-analytic audiences.
- Masters in in Economics, Statistics, Mathematics or directly related field and at least 5 years of professional post-graduate experience in constructing, validating, and executing predictive modeling solutions. (PhD is highly preferred)
- Strong background in statistical languages technologies such as R, Python, SAS, etc.
- Experience with computer development languages (Java, C++).
Preferred skills and experience:
- Advanced skills and training in machine learning data mining and other quantitative research analytics such as: Non-Linear Regression Analysis, Multivariate Analysis, Bayesian Methods, Generalized Linear Models, Decision Trees and Random Forest, Non Parametric estimations, Neural Networks, Ensemble Models, etc.
- Experience in translating business problems across disciplines into advanced analytic projects with measurable business value.
- Experience with theoretical modeling approaches and matching analytic modeling approaches to a wide range of business applications.
If interested please forward resumes to email@example.com