Research, customization, and development of statistical and machine learning algorithms to meet distinctive and complex project requirements that have broad business impacts; tasks include defining hypotheses, undertaking important tests and experiments, evaluating, adjusting and enhancing algorithms and methods to particular scenarios.
Analysis of big data for data-driven solution, validation, evaluation and technology innovative remedies.
Optimize data to analyze processes and systems for better efficiency and tracking.
Coordinate with various functional groups to implement models and monitor results.
Leading project teams to achieve targets and objectives.
forseeing challenges and issues and suggesting process, product, and service improvements.
Work with stakeholders throughout the firm to point out opportunities for leveraging company data to drive business solutions.
cooperate with management, stakeholders, and teams to define technological roadmaps.
Mentoring and training subordinate team members and serving as a practical role-model for statistics, artificial intelligence, and machine learning.
composing documents that clearly proves to be a guidance on how algorithms should be implemented, verified, and validated.
Composing Articles for use in the preparation of intellectual property and technical publications.
Monitoring the literature (for Article purposes) of interest and industrial development trends broadly in the areas of data analysis and machine learning.
Qualifications And Experience
Expert in statistical analysis methods, including analysis of variance, regression, time series analysis, survival analysis, etc.
Thorough knowledge in artificial intelligence and basic machine learning theoretical know-how and data mining technologies.
Broad knowledge of data engineering or informatics systems.
Leadership and hands-on experience with the development of data analytics systems, including data exploration/crawling, feature engineering, model building, performance evaluation, and online deployment of models.
hands-on experience in R- programming and Languages like Python.
Hands on experience of using Hadoop, Spark, Hive, Pig or Storm, etc.
Strong database skills and experience, including experience with SQL programming.
Knowledge in big data technologies, cloud computing/distributed computing, data fusion, and data visualization.
Satisfactory technical report writing and presentation skills.
Optimization of algorithm complexity vs. accuracy vs. implementation cost.
Implementing robust software for use in research programs with a minimum of review and other formal processes.
A degree in Computer Science, Engineering, Statistics, Applied Mathematics, or related fields. Minimal 8 years' industry or academic experience in data science.