Analyst Data Science

Job Description And Responsibilities

Position Summary

The Data Scientist is an Analyst level role in the Sub-Saharan Africa (SSA) team and positioned within the Visa Consulting & Analytics (VCA) business unit. VCA primarily provides data driven consulting services to Visa clients globally. We are seeking an innovative and analytical thinker to execute on our data-driven strategies for the SSA sub-region. As a Data Scientist, you are expected to generate data and business insights, develop predictive and prescriptive models, context-based prototypes, and high impact storyboards to promote a data-driven strategy and solutions approach for Visa and its clients. The role is based out of our Nairobi, Kenya office and is hybrid in nature requiring at least 50% physical presence in the office.

Principal Responsibilities

Serve as an analytics expert in designing, developing, and implementing best in class analytic solutions. Create and deliver powerful insights from data through better visualization and storyboarding. Collaborate with internal and external partners to fully understand business requirements and desired business outcomes. Demonstrate execution proficiency in handing multiple medium-to-large analytics projects in a team environment that includes the rest of the Data Science team. Draft detailed scope for assigned projects, addressing suggested methodology and analytics plan. Execute on the analytics plan with appropriate data mining and analytical techniques. Perform quality assurance of data and deliverables for work performed by other Data Scientists and self. Ensure all project documentation is up to date and all projects are reviewed per analytics plan. Ensure project delivery within timelines and budget requirements. Build on teamâs analytical skills and business knowledge. Enhance existing analytics techniques by promoting new methodologies and best practices in the Data Science field. Provide subject matter expertise and quality assurance of complex data-driven analytic projects.

Qualifications

Post-graduate degree (Masters or PhD would be an advantage) in a Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, Engineering, or equivalent.

Professional Experience

Minimum of 3-4 years of analytics expertise in applying statistical solutions to business problems Experience working in one or more of the Card Payments markets around the globe would be a distinct advantage. Good understanding of the Payments and Banking Industry including aspects such as consumer credit, consumer debit, prepaid, small business, commercial, co-branded and merchant payment solutions. Good knowledge of data, market intelligence, business intelligence, and AI-driven tools and technologies. Experience planning, organizing, and managing multiple large projects with diverse cross-functional teams. Demonstrated ability to incorporate new techniques to solve business problems. Demonstrated resource planning and delivery skills.

Technical Expertise

Expertise in distributed computing environments / big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.) Ability to write scratch MapReduce jobs and fluency with Spark frameworks Familiarity with both common computing environments (e.g. Linux, Shell Scripting) and commonly-used IDEâs (Jupyter Notebooks); proficiency in SAS technologies and techniques Strong programming ability in different programming languages such as Python, R, Scala, Java, Matlab, C++, and SQL Familiarity with solution architecture frameworks that rely on APIâs and microservices Familiarity with common data modeling approaches, and ability to work with various datatypes including JSON, XML, etc. Ability to build data pipelines (e.g. ETL, data preparation, data aggregation and analysis) using tools such as NiFi, Sqoop, Ab Initio; familiarity with data lineage processes and schema management tools such as Avro Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Markov Chain Monte Carlo, Gibbs Sampling, Evolutionary Algorithms (e.g. Genetic Algorithms, Genetic Programming), Support Vector Machines, Neural Networks, etc. Expert knowledge of advanced data mining and statistical modeling techniques, including Predictive modeling (e.g., binomial and multinomial regression, ANOVA); Classification techniques (e.g., Clustering, Principal Component Analysis, factor analysis); Decision Tree techniques (e.g., CART, CHAID) Deliver results within committed scope, timeline and budget Very strong project management skills and experience Ability to travel within the SSA and CEMEA Region.

Business Experience

Results-oriented with strong problem solving skills and demonstrated intellectual and analytical rigor Good business acumen with a trackrecord in solving business problems through data-driven quantitative methodologies. Experience in payment, retail banking, or retail merchant industries is preferred Team oriented, collaborative, diplomatic, and flexible style Very detailed oriented, is expected to ensure highest level of quality/rigor in reports and data analysis Proven skills in translating analytics output to actionable recommendations and delivery Experience in presenting ideas and analysis to stakeholders whilst tailoring data-driven results to various audience levels

Leadership Competencies

Demonstrates integrity, maturity and a constructive approach to business challenges Role model for the organization in showcasing core Visa Values Respect for the Individuals at all levels in the workplace Strive for Excellence and extraordinary results Use sound insights and judgments to make informed decisions in line with business strategy and needs Leadership skills include an ability to allocate tasks and resources across multiple lines of businesses and geographies. Leadership extends to ability to influence senior management within and outside Analytics groups. Ability to successfully persuade/influence internal stakeholders for building best-in-class solutions. Team oriented, collaborative, diplomatic and flexible style. Exhibits intellectual curiosity and a desire for continuous learning.

Additional Information

All your information will be kept confidential according to EEO guidelines.