Senior Data Scientist - Careem Pay
At Careem, our mission is to simplify and improve the lives of people and create an awesome organisation that inspires. With this vast mission statement, we started by improving transportation and delivery in the region, and now we are expanding into Payment and we’ve launched a super-app, hosting multiple Careem and 3rd-party apps, to further simplify and improve people’s everyday life.
We built the first multi-billion dollar tech startup in the MENAP region. The first line of code was written in Pakistan and we built on it further in Dubai and Berlin. We operate in 100+ cities across 11 countries. We joined Uber officially in early 2020. We grew and attracted top global talent and grew a culture for bold ambitions, shooting for the moon, innovation with tight constraints, and being Careem/gracious.
As a Data Scientist at Careem, you'll be part of a team that's leading the next wave of disruption at a whole new scale. You will be developing descriptive and predictive models as well as running extensive data analysis on millions of customer transactions supported by a cutting edge data platform to unlock the big opportunities that simplify the lives of people through reliable transportation. Some of the problems the data science team works on are: Dynamic pricing optimization. Optimal dispatching. Fraud detection and prevention. ETA prediction. Location search optimization.
- Build a long-term vision on how we can rethink our customer acquisition and engagement strategies leveraging data in our decision making.
- Drive exploratory analysis to understand the ecosystem, user behavior; identifying new levers to help move metrics and build models of user behaviors for analysis and product enhancements.
- Shape and influence data/ML models and instrumentation to optimize the product experience and generate insights on new areas of opportunity and new products.
- Provide product leadership by sharing data-based recommendation to communicate state of business, root cause of change in metrics and experimentation results influencing product and business decision
- Implement scalable machine learning algorithms that will be used in production on big data.
- Embark on exploratory data analysis projects to achieve better understanding of phenomena as well as to discover untapped areas of growth and optimization.
- Answer complex analytic questions from big data sets to help Careem shape its products and services in a better way.
- Help define and track the appropriate key metrics for specific projects.
- Design and run randomized controlled experiments, analyze the resulting data and communicate results with other teams.
- You will always challenge the status quo and continually investigate new data processing technologies and seek to ensure that we follow the industry best practices.
- 6+ years experience in data mining, predictive modeling, time series analysis, machine learning, Big Data methodologies, transformation and cleaning of both structured and unstructured data.
- Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering or Computer Science.
- Strong problem solving and coding skills.
- Strong experience in leading cross-functional teams and projects from a technical and data science perspective.
- Solid knowledge of and experience with the payment channels, pay terms, banking and payments services, and the payments regulatory landscape, preferably in MENA region
- Solid understanding of digital wallet use cases and potential risks associated with them
- Fluency in English along with excellent oral and written communication skills.
- Proficiency and demonstrated experience in at least 2 of the following: Python, R, SQL, Spark, Hive.
- Demonstrated experience with database technologies (e.g. Hadoop, BigQuery, Amazon EMR, Hive, Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL) is a plus.
- Demonstrated experience with business intelligence and visualization tools (Tableau, MicroStrategy, ChartIO, Qlik) along with geospatial data processing skills is also a plus.
- Knowledge of Agile methodologies.