26 May 2023
Full-Time Data Scientist, Spotify Advertising – Al-Manṣūrah
Data Scientist needed. As a Team member, you’ll collaborate with specialists to build safe systems and solutions. Our culture values intellectual curiosity, cognitive variety, and bringing your complete self to work. Our people are creating history. Come work with us.
Job Title : Data Scientist, Spotify Advertising
Location : Al-Manṣūrah, Al-Daqahliyyah, Egypt
Salary : $ 43.9 per hour.
Company : pymetrics
Job Type : Full-Time
- Using supervised and unsupervised machine learning approaches, uncover and operationalize the underlying structure and connections contained within the data.
- Manage your own process by identifying and implementing high-impact projects, prioritizing requests from outside parties, and ensuring that the project is completed on schedule so that the results may be put to good use.
- Discovers and takes advantage of opportunities for improvement. Encourages taking risks, exploring different approaches, and learning inside the business. demonstrates a commitment to change via both actions and words. Helping people adapt to change while facing pressure and uncertainty is rewarding.
- Data analysis gives the development team new ideas. Solve business problems using statistics and machine learning. A fast-moving firm with many teams and customers.
- Aside from supplying information on Product & Tech activities, you’ll come up with fresh product growth possibilities and build momentum via influence. Hands-on arithmetic and critical thinking must be balanced in order to be effective.
- 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.
- The outcomes of an analytical model should be analyzed, interpreted, and summarized. Work with complicated business reports to assist in their understanding and context Simulates different outcomes depending on various circumstances and assumptions. Identifies deviations from defined boundaries and ranges, as well as positive and negative trends and measurements. Analyzes existing patterns and makes predictions about the future to find prospective problems. Analyzes data in terms of statistics and finance.
- Perform data analysis by using structured query language (SQL), scripting languages (such as R or Python), and internal dashboards. Conduct research on the buying patterns of prior customers and the data from previous sales in order to make certain suggestions.
- Adept in utilizing huge data sets to identify possibilities for product and process improvement, as well as models to assess the efficiency of various courses of action, with a demonstrated ability to generate business outcomes via database insights.
- Exhibits great time management abilities as well as the capacity to work autonomously. Multitasks and prioritizes everyday chores and processes. Completes department and individual job-related objectives on schedule and at a high standard.
- An advanced degree in computer science or a related technological discipline and five years of relevant work experience are also acceptable qualifications.
- If you have a Master’s degree in Statistics (or a related quantitative topic), you will be required to have at least two years of experience working in a job that is comparable to the one you are applying for. Expertise in predictive modeling, analytics for large amounts of data, exploratory data analysis, and machine learning.
- The ability to work with large datasets in statistical programming languages (Python, R, etc.) A familiarity with D3.js, matplotlib, etc. is desired. Random Forest, SVM, k-NN, Nave Bayes, Gradient Boosting, and other machine learning algorithms are a bonus.
- Diplomacy and trust are required for the capacity to inspire or persuade. To thrive in this role, you must collaborate successfully with persons within and outside the organization. To do one’s duties effectively, one must constantly interact with other departments and divisions in order to address problems, offer information, and find solutions.
- Natural Language Processing, Information Retrieval, Machine Comprehension, Question Answering/Conversational AI, Reinforcement Learning, Knowledge Graph, Causal Inference, and Experiment Design are among the quantitative domains in which you should be well-versed.