The Data Scientist utilizes a diverse range of data-focused skills, experience, deep technical and analytical problem solving, and team-centered solutioning for complex problems.
This position requires strong attributes for problem solving, data analysis, troubleshooting.
Collaborate with dynamic team of engineers, developers, and scientists who research and integrate algorithms to develop solution to address complex data problems and support development.
Essential Job Functions:
Participate in all phases of the analytic lifecycle, from research design, data collection and data processing to model building, deployment and presentation of results.
Assess project requirements and develop data analysis algorithms.
Contribute to technical solutions and implement software analyses to unlock the secrets held by big data sets.
Responsible for Developing/supporting Artificial Intelligence, Machine Learning, and Data Science solutions for Product Development.
Rapidly prototype new ideas and methods to deliver quality code that is testable and concise.
Use AI/ML technologies to innovate solution to existing problems for the team.
Engage developers to share their opinions, knowledge, and recommendations to meet the deliverables.
Fully proficient with common statistical and machine learning techniques and exhibit some knowledge of advanced modeling techniques and their application.
Work with Team members to craft an analytic strategy that meets their needs and delivers timely results
Integrate relevant internal and external research findings to generate hypotheses and help Team members make informed decisions.
Participate in all phases of the analytic lifecycle, from research design, data collection and data processing to model building, deployment and presentation of results.
Setting up Experiments, Data acquisition, data processing and report generation with visualization.
Experience:
Greater than four (4) years of relevant work experience.
Building and deploying machine learning and/or statistical models.
Knowledge of multiple quantitative research and analysis approaches and their tradeoffs.
Reading/writing/speaking about predictive modeling to stakeholders ranging from Team members to modeling experts.
Solid working knowledge and experience with Microsoft Office and other related Business applications (e.g., MS Word, MS Excel, MS Access, MS PowerPoint, Outlook, Internet, etc.).
Proficient in programming in C/C++, Python, R, SQL, or any other transferrable language (MATLAB, Java, etc.)
Education:
Bachelor's degree or Master's degree in Computer Engineering, Computer Science, Mathematics, Electrical Engineering, Information Systems, or IT, or an equivalent combination of education and relevant experience.