17 Mar 2023
Full-Time Lead Data Scientist, Growth & Engagement – Al Khurma
We need clever, interested, technically competent data scientists. We recruit the sharpest minds and provide them access to cutting-edge technology. In this job, you’ll develop new ideas and solutions to increase our capacity to target the correct audience, extract insights, and measure marketing efforts. You’ll use our data and machine learning to fuel your ideas.
Job Title : Lead Data Scientist, Growth & Engagement
Location : Al Khurma, Mecca, Saudi Arabia
Salary : $ 43.11 per hour.
Company : Ontra
Job Type : Full-Time
- It’s up to you to take charge of your own workflow by identifying and carrying out high-impact initiatives, setting priorities for requests from other departments, and making certain projects are completed on time.
- 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.
- Attempt to describe the results of a simulation. Aids in the understanding of difficult business reports. Experiment with a variety of possible outcomes. Procedures and exceptions deemed unacceptable have been noted. Recognizes potential problems based on current trend projections. Data and budgets are examined.
- It is feasible to find and operationalize the data’s underlying structure and connections using supervised and unsupervised machine learning approaches.
- Enhances performance by translating current knowledge into continuous improvement actions. Collects and analyzes information or data on present and future best practice trends. Seeks information on factors affecting the advancement of organizational and process-related factors.
- Creates and acts on improvements. Encourages risk-taking, experimentation, and organizational learning. Actions and words show change commitment. Under stress and uncertainty, helps people accept change.
- Skilled in the use of huge data sets to identify possibilities for product and process improvement and models to assess the efficacy of multiple courses of action, along with a demonstrated ability to generate business outcomes using database insights.
- By using data analysis, the development team is able to come up with new ideas. Analyze business problems using statistical and machine learning approaches. Having a high number of employees and customers allows an entrepreneurial business to move swiftly.
- Excellent time management and independence abilities. Prioritizes daily duties and procedures and is capable of multitasking. Completes departmental and individual goals on time and with excellent results.
- In addition to providing insights on Product & Tech operations, you’ll help develop new product growth prospects and momentum. Analytical skills like as SQL, R, Python, and Tableau need to be matched with critical thinking.
- PhD in Computer Science with Virtual Assistant/Natural Language Processing research papers OR Master’s in Computer Science, Statistics, Data Science, or similar technical subject with five years of relevant employment experience.
- 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.
- Diplomacy and trust are necessary to inspire or persuade. To thrive in this role, you must collaborate successfully with both internal and external stakeholders. To do one’s duties effectively, one must constantly interact across departments and divisions in order to address problems, offer information, and find solutions.
- If you have a Master’s degree in Statistics (or a related quantitative subject), you’ll need at least two years of experience in a similar position. Predictive modeling, big data analytics, exploratory data analysis, and machine learning expertise.
- Utilizing statistical programming languages to do analysis on huge datasets (Python, R, etc.) A working knowledge of D3.js, matplotlib, and other similar programs is preferred. It is a wise decision to implement several machine learning strategies, such as Random Forest, SVM, k-NN, Nave Bayes, and Gradient Boosting.