9 Feb 2023
Full-Time Nielsen Sports Data Scientist – Jhang
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 : Nielsen Sports Data Scientist
Location : Jhang, Punjab, Pakistan
Salary : $ 44.68 per hour.
Company : Meta
Job Type : Full-Time
- Has good time management abilities and can operate independently. Multitasks and prioritizes everyday work. Meets department and individual objectives on schedule and well.
- Improves effectiveness by using the most current information available Collects and analyzes data on existing and future best practice trends. Find out what’s going on with organizational and process difficulties that are affecting their success.
- SQL, programming languages such as R or Python, and internal dashboards should all be used for data analysis. Conduct research on past buying patterns of customers and sales data, then make actionable suggestions.
- The development team can come up with fresh concepts thanks to data analysis. Solve business challenges using statistical and machine learning techniques. An entrepreneurial company with a large number of teams and consumers is able to operate quickly.
- 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.
- Our proven ability to generate business results using databased insights enables us to leverage massive data sets to identify strategies to improve products and processes, as well as models to estimate how advantageous various actions are.
- Using supervised and unsupervised machine learning techniques, it is feasible to discover and operationalize the underlying structure and connections of the data. This may be accomplished. It is not impossible to accomplish this goal.
- Interpret and summarize model findings. Helps comprehend complicated business reports. Does what-if scenarios with varied inputs. Unacceptable procedures and exceptions are identified. Recognizes prospective issues based on existing trend estimates Analyzes statistics and finances.
- With your knowledge of product and technology operations, you’ll also be able to contribute to the development of new product growth possibilities and momentum. SQL, R, Python and Tableau are excellent analytical tools, but they need to be used in conjunction with critical thinking abilities.
- Finds ways to keep getting better and takes action on them. Encourages taking calculated risks, trying out different ways of doing things, and organizational learning. Shows through actions and words that they are willing to change. During times of stress and uncertainty, helps others accept change.
- AI is growing stronger at information retrieval, machine comprehension, answering questions/conversational AI, reinforcement learning, knowledge graphs, causal inference, and experiment design.
- Computer Science PhD or Master’s degree in Computer Science, Statistics, Data Science, or a similar technical subject with five years of relevant work experience in the field.
- Data manipulation and analysis using statistical computer languages (Python, R, etc.) is desired. Prior knowledge of data visualization technologies such as D3.js, matplotlib, and the like is desirable. A thorough knowledge of machine learning methods such as Random Forest, SVM, k-NN, Nave Bayes, and Gradient Boosting is an asset in this position.
- 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.
- Confidence, diplomacy, and trust are required to inspire or per Work successfully with people within and outside the company to be successful in this role. Effective work requires constant cross-departmental communication to solve problems, share information, and brainstorm solutions.