Assistant Vice President, Data Science

4 days ago

Doha, Baladīyat ad Dawḩah, Qatar Qatar National Bank Full time

Established in 1964 as the country's first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.

QNB Group's presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.

QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poor's (A), Moody's (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.

Based on the Group's consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.

QNB Group has an active community support program and sponsors various social, educational and sporting events.

Job Purpose Summary:

The data scientist will collaborate with business and operational leaders to provide expert support through leveraging data and analytical tools, strategic thinking, and hypothesis-based analysis on machine learning (ML)-based projects. The data scientist is responsible for modelling complex business problems through statistical, algorithmic, mining, and visualization techniques. Further, he will support senior leadership through oversight of business insights, reports, and analyses to aid in the decision-making process.

Essential Duties & Responsibilities:
  • Oversee and develop predictive models using various machine learning techniques.
  • Research and implement cutting-edge techniques and tools in machine learning / deep learning / artificial intelligence to make data analysis more efficient.
  • Identify and implement new statistical or other mathematical methodologies as needed for specific data science initiatives.
  • Build data-driven models to answer business questions, and perform large-scale experimentation, analysis, and visualization techniques to deliver more efficient and repeatable data science insights.
  • Integrate domain knowledge into the Data Science solutions (e.g., from an understanding of financial risk, customer journey, quality prediction, sales, marketing).
  • Continuously monitor execution and health of Data Science models, to ensure efficient and high-quality outputs are attained.
  • Establish best practices for ML development and production infrastructure (e.g., cloud, Spark, GPUs, containers).
  • Design and conduct data analyses with the highest standard of rigor and scientific accuracy; this includes study design, methodology, algorithms, and statistical modelling.
Education & Experience Requirements:
  • University graduate preferably with a Major in computer science, data science, software engineering, information systems, or related quantitative field.
  • At least 10 years of relevant experience, preferably within a Data Scientist or related role.
  • A PhD in statistics, ML, computer science or the natural sciences, especially physics or any engineering disciplines or equivalent, would be desirable.
  • Candidates must have a specialization in ML, AI, cognitive science or data science.
  • Excellent oral and written communication skills (including report writing) in English and Arabic.
  • Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and BI.
  • Advanced SQL knowledge and experience working with relational databases.
  • Experience with data pipeline and workflow management tools (ETL, Airflow, etc.) and big data tools (Hadoop, Spark, Kafka, etc.).
  • Using one of the following modelling programs effectively: Python, Golang, Ruby, Perl, Scala, Java, SAS, R, MATLAB, C, and C++, etc.
  • Interested in big data, machine learning, deep learning and artificial intelligence subjects.
  • Open-minded point of view and strong problem-solving skills.
  • Excellent business acumen and interpersonal skills; able to work across business lines at a senior level to influence and effect change to achieve common goals.
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