Job Overview: Senior Data Scientist
To produce innovative solutions driven by exploratory data analysis from Labcorp's vast, complex and high-dimensional datasets. Apply knowledge of statistics, data modeling, data sciences and artificial intelligence to recognize patterns, identify opportunities and make valuable discoveries to support Labcorp's mission to improve human welfare. Use a flexible, analytical approach to design, develop, and evaluate predictive models. Generate and test hypotheses.Education/Qualifications:
- Advance degree is required in Computer Science, Engineering, Statistics, Math or related field
- Must be able to provide evidence of relevant research expertise in the form of presentations, software, technical publications, and/or knowledge of applications.
- Master with at least 5 years' experience or Ph.D. with 3 years' of experience in a Data science setting.
- Proven data science leveraging time series techniques such as ARIMA, SARIMA, exponential smoothing, autoregression modeling, etc.
- Background in a financial or closely related field performing data science analysis (such as energy, oil, trading, etc.).
- Learn to develop novel ways of integrating, mining and visualizing diverse, high dimensional and poorly curated data sets.
- Demonstrated solutions and impact taking routine data and finding the extraordinary through machine learning, AI, classical statistical techniques, and deep learning.
- Develop novel ways for information retrieval from unstructured data such as medical records or laboratory reports.
- Deliver advanced machine learning techniques and transformative and generative modeling approaches applied to time series such as CNN's, RNN's, LSTM's, and Transformer networks.
- Apply advanced techniques to practical solutions such as enterprise data initiatives and causal modeling of diseases.
- Develop and deliver presentations to communicate technical ideas and analytical findings to non-technical partners and senior leadership, including underwriters and IT professionals
- Build underlying software infrastructure to better manage, integrate and mine the data that Labcorp processes on a daily basis.
- Work closely with engineering teams and with some supervision participate in the full development cycle from product inception, research and prototyping to release in production.
- Interpret data and learn how to present to others the stories they represent through rich and intuitive visualizations.
- Write production quality code while implementing your own ideas.
- Experience in artificial intelligence and statistical learning, with targeted areas for time series and financial use cases.
- Experience with statistical methodologies and machine learning techniques such as: neural networks, graphical models, ensemble methods and natural language processing
- Experience with multiple deep learning techniques such as CNN, LSTM, RNN, etc., in addition to standard machine learning approaches such as those found in scikit-learn.
- Master of evaluation techniques for supervised and unsupervised techniques. Knows to evaluate the quality of data and determine gaps in data or assumptions.
- Proficiency with Python. Can develop meaningful python code using objective oriented programming and functional programming. Writes tests for code. Can debug errors quickly.
- Strong data visualization skills.
- Familiarity with one or more machine learning libraries or frameworks such as: PyTorch, Tensorflow.
- Experience with rational and non-structure databases is highly desirable.
- Experience using cloud technologies such as AWS with tools such as S3, EC2, Lambda, Athena, etc.
- Demonstrated success in technical proficiency, scientific creativity, collaboration with others and independent thought.
- Ability to collaborate with the team and translate existing research into practical solutions and products ability to build and manage relationships with various collaborators across and outside the company.
- Comfortable working with both technical and non-technical staff to translate concepts and algorithms into working prototypes.
- Drive project execution and implement a robust plan for measuring success
- Lead discussions with senior leadership at the department or functional level
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