Manager, Data Science at MTN Mobile Money: (Deadline 8 September 2023)
- Provide machine learning models, reports and analysis to support and contribute to the development of the functional BankTech strategy in line with the overarching business goals,
- Help shape the strategic direction of Mobile Money via data-driven decisions and analytically identified opportunities.
- Perform complex data discovery utilizing AI and machine learning on large scale data lakes such as daily transaction data, KYC and GSM Data
- Ensure accurate and timely reporting to enable the regular review of the functional strategy, roadmap and performance to ensure its alignment with the changing dynamics of the internal and external ecosystem.
- Stay current with the latest industry trends, tools, and technologies in data science and machine learning, and identify opportunities to apply them to drive innovation
- Support and lead the design, develop and deployment of machine learning based platform for BankTech services and other relevant use cases
- Responsible for deployment of infrastructure components to enable use of the state-of-the- art techniques in Artificial Intelligence and Machine Learning
- Support and manage end-to-end machine learning model integration with Mobile money data lakes
- Work with business units to understand requirements and create plans to address them. Specifically possess the ability to translate requirements of non-technical stakeholders into actionable data science projects.
- Establishes and maintains effective performance tracking; identify improvement opportunity, form hypothesis, propose, design and implement tests to drive strategy enhancement and optimization.
- Delivers effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
- Develops and automates reports, iteratively build and prototype dashboards to provide insights at scale, solving for analytical needs. Facilitates implementation of work product and ensure accuracy.
- Ensures standard work processes and documentation requirements are timely and consistently followed by team.
- Encourages continuous improvement of team processes and share across functional teams to ensure consistency.
- Manage extension of company’s data with third party sources of information when needed in line with the legal & regulatory governance frameworks & policy.
- Ensure machine learning solutions are compliant with infrastructure, information security , privacy, banking regulations & regulatory requirements.
- Security and virtual network peering of the scoring API in line with best practice.
- Manage the processing, cleansing, and verifying the integrity of data used for analysis.
- Perform ad-hoc analysis and presenting results in a clear manner.
- Develop actionable insights to provide future based guidance to drive product performance and revenue.
- Collaborate with Data Engineering team to build data pipelines for machine learning.
- Maintain budget allocation across the services and resources of the machine learning platforms.
- Perform any other tasks that may be assigned by the supervisor.
- Minimum of 4-year tertiary degree in Computer Science, Mathematics, Statistics, Data
Science or related field. - Master’s Degree in a Financial, Commerce, Statistical or related field (preferred)
- MBA or Masters (advantageous).
- AI/ML Professional certification is an added advantage.
- 5 or more years of relevant work experience as a Data Scientist.
- At least 3 years’ experience within a non-traditional FinTech, Banking or Financial
Services Sector. - Experience in deploying data science models in a machine learning platform role.
- Experience in ML Ops within banking or financial services industry is advantageous.
- Experience with Machine learning platforms and deploying and monitoring machine
learning solutions and applications. - Experience in building architectures around Machine Learning systems.
- Proven experience with ML model management platforms, like MLFlow, wandb.ai, or
Sagemaker or KubeFlow. - Proficiency in developing production micro-services and APIs.
- Strong knowledge of containerization and orchestration technologies (Kubernetes,
docker). - Deep understanding of Cloud and on-premise deployment of Machine learning.
- API experience and understanding of microservices and Kubernete infrastructure.
- Experience of working in an Agile/DevOps environment
- Proficiency in working with Python (Numpy, Scikit-learn, Pandas, Scipy, Matplotlib,
Tensorflow, Keras, Seaborn, Bokeh), SAS or R / Scala for data clean up and advanced
data analytics - Working knowledge in Hadoop, Apache Spark and related Big Data technologies
(MapReduce, PIG, HIVE) - Demonstrated experience utilizing software tools to query and report data: SAS
(Enterprise Guide and/or programming), tableau, Power BI,D3 VBA, SQL, and Business
Objects - Highly proficient in database management systems like Postgres, Oracle, Mongo,
MSSQL - Experience in ecommerce and electronic payment business is advantageous
- Experience working across global locations/ regions and have a grasp of political, social,
infrastructure and integrity challenges.
All interested candidates are requested to send their application letters and updated curriculum vitae together with copies of their academic credentials no later than 08th September 2023. Through the job application platform or send an email with requirements to: jobs2.RW@mtn.com.
We strongly encourage applications from women and/or individuals with disabilities.
Note: Only qualified applicants will be contacted within 14 days of their submission.
MTN Rwanda PLC is an equal-opportunity employer.
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