Full-Time Data Scientist, Small Business Group – Al Farwānīyah
Data Scientist needed. This person will manage high-profile data science and AI initiatives across several business units and teams to build AI-based solutions. Candidate must be comfortable working with existing and upcoming AI technologies in a fast-paced, unexpected, and ambiguous setting. The duties include data collecting, processing, exploratory data analysis, measurement, unstructured data analysis, predictive analytics, prescriptive analytics, interpretation, presentation, and system installation. The ideal applicant can assist high-quality initiatives in numerous areas. They must have a track record of ensuring data quality and be team players who thrive in high-performing environments. As a Data Scientist, you’ll boost the organization’s analytics and data science capabilities for employee benefit solutions.
Job Title : Data Scientist, Small Business Group
Location : Al Farwānīyah, Al Farwānīyah, Kuwait
Salary : $ 42.11 per hour.
Company : HopHR
Job Type : Full-Time
- Transforms current knowledge into performance-boosting continuous improvement initiatives. Collects and analyzes data on present and future best practice trends and trends. Seek details about organizational and process concerns affecting growth.
- Review the outcomes of the analytical model and synthesize your findings. Work with complicated business reports to help analyze and put them in perspective Based on a variety of parameters and assumptions, what-if simulations are run. It identifies anomalies, anomalous patterns, and metrics that are out of the specified range of acceptable values. Analyzes present patterns and future predictions to identify possible problems. The statistical and financial analysis of data is the responsibility of the person in question.
- To be in charge of your own workflow, you need to find and implement high-impact projects, put requests from third parties in order of importance, and make sure projects are finished on time so that the results can be put to good use.
- Collaborate with development team to suggest data-driven improvements. Apply statistical and machine learning approaches to business data. Work in a fast-paced, entrepreneurial atmosphere with different teams and clients.
- In addition to providing insights on current Product & Tech activities, you will generate innovative product growth prospects based on findings and drive momentum via your influence. You must find a mix between critical thinking and hands-on analysis utilizing tools and packages such as SQL, R, Python, Tableau, etc.
- Identifies and takes action on possibilities for continual development. Risk-taking, alternative techniques, and organizational learning are all encouraged by this policy. Demonstrates a personal commitment to change by doing and talking about it. In times of stress and uncertainty, you may help people embrace change by offering support and guidance.
- Scripting languages (such as R or Python) and internal dashboards may all be used to do data analysis tasks. Make recommendations based on past customers’ purchasing habits and sales data. Do research.
- Using supervised and unsupervised machine learning, uncover data structure and correlations.
- Possesses outstanding time management abilities and the capacity to work autonomously. Prioritizes everyday activities and processes and is capable of multitasking. Completes departmental and individual objectives on schedule and with high-quality output.
- Proficient at using large data sets to find ways to improve products and processes, as well as models to see how well different actions work. Proven ability to drive business results with database insights.
- Having worked with and analyzed large data sets in statistical computer languages (Python, R, etc.) It would be best if you had experience with D3.js, matplotlib, etc. Methods for machine learning like Random Forest, SVM, k-NN, Nave Bayes, and Gradient Boosting are good.
- Master’s degree in Statistics, Computer Science, Mathematics or other quantitative field essential, 2-3 years in equivalent function (Master’s Degree). Predictive modeling, big data analytics, exploratory data analysis, and machine learning experience.
- Information retrieval, machine understanding, question answering/conversational AI, reinforcement learning, knowledge graphs, causal inference, and experimental design: natural language processing
- Computer science PhD with substantial Virtual Assistant/Natural Language Processing research publications OR computer science, statistics, data science, or a related area of study master’s degree with five years of relevant experience.
- The capacity to encourage or persuade people is a big aspect of the profession, which requires a substantial amount of diplomacy and trust. To be successful in this role, you’ll need to be able to work well with people on both the inside and outside of the organization. To do one’s job well, one must constantly engage in interactions that need extensive discussion of issues, the dissemination of information, and finding solutions across several departments and divisions.