As a Lead Data Scientist/Machine Learning Engineer and ALEF Education, you should have exposure to work in a fast-paced Agile IT environment.
Your main responsibility is to build complex data processing pipelines, design and implement machine learning algorithms. You will help envision our machine learning strategy at scale and help build the future of Education Science.
As a member of our data science and machine learning team, you will be interacting with multi-functional teams for data preparation and apply machine learning/data mining algorithms in efficient workflows to process large-scale data.
The Lead Machine learning role will be responsible for both managing a team and delivering projects from end-to-end: problem statement and conceptualization, proof-of-concept, and participation in final deployment. You will also perform ad-hoc statistical and data science analyses where required.
Job Specific Responsibilities
- Provide technical leadership to internal and external stakeholders
- Provide Technical authority in prospective meetings with other departments, evaluate technical proposals from suppliers, and implement recommendations to stakeholders.
- Provide Hands-on Technical leadership, in development, operation and improvement of services. Work closely with the wider team to ensure high quality code is delivered in line with the project goals and delivery cycles.
- Work with product managers to understand user needs for new/existing services.
- Work with delivery teams breaking technical requirements down, identify API requirements for integration with internal/external systems.
- Proactively advice on best practices.
- Lead the design and prototype of data
- Lead the design and prototype algorithms that run on cloud based big data environments, identify technical options/inform architectural approaches, working with team members to write tests, code and documentation for new/existing systems.
- Develop and maintain data infrastructure systems that power statistical and machine learning models on large-scale datasets.
- Understand algorithms (be able to tweak them when needed) as well as infrastructure that enables fast iterations
- Manage development teams
- Assist in the budgeting process.
- Manage development team, providing feedback and managing performance.
- Identify opportunities for new algorithms and hardware improvements for future products.
- Work closely with Data science, Data engineering and Feature teams.
- Identify new ideas to build and evolve machine learning solutions
- Own data quality throughout all data lifecycles, including acquisition, cleaning, processing, and validation.
- Build platforms to facilitate the rapid iteration of machine learning and optimization algorithms.
- Identify new ideas to build and evolve Machine Learning solutions, develop new features and benchmark possible solutions.
- Engineer new features to improve algorithm predictions
Education, Experience and Required Skills
Educational Qualification: Degree in Statistics, Computer Science or related preferred
- Minimum 8 years
- Experience in productionizing data-driven algorithms
- 5 + years of strong data analysis skills, including principal component analysis, working with Recurrent neural networks
- Experience working with educational data sets.
- Experience in working on large datasets related to industry verticals, preferably Education Science
- Experienced user of Python libraries such as scikit-learn, scipy, NetworkX, Spacy, and NLTK.
- Working experience of deep learning and transformer algorithms and workflows, and experience with any of the frameworks like Torch, Caffe, MXNet, TensorFlow.
Technical Skills Required (Insert Level of Expertise Here)
- Comprehensive and recent experience designing and implementing complex software systems, i.e. is an active ML Engineer currently engaged in architecting and building high-volume digital services.
- Knowledge of Agile product management, in particular determination of vision, objectives, goals and success criteria.Hands on experience with Python, R, Scala, Java
- Exposure to machine learning frameworks: Tensorflow, Keras, Pytorch, MXNet
- First-hand with a variety of machine learning and pattern recognition techniques
- AWS or similar cloud platform exposure
- Knowledge of the git version control system.
- Good Knowledge and experience in NLP, NLU
- Knowledge in Spark, Hive, Cassandra, Kafka and NoSQL databases is plus
- Develop in Jupyter (IPython) notebook, Spyder and various IDE
Leadership and Operational Skills Required
- Proven capability in managing technology implementation projects and in presenting to/working with stakeholders at every level of seniority.
- Ability to meaningfully present results of analyses in a clear and impactful manner
- Outstanding ability to develop efficient, readable, highly optimized/maintainable and clear code.
- Organized, detail-oriented and pragmatic
- Thrives in both independent work and in collaboration on a multi-disciplinary team
- Intuitive ability to see a complex problem from many perspectives
- Excellent communication skills in English and Arabic.
- Ability to quickly research and learn new programming tools and techniques.