|JobFamilyName: Information Technology
Target start date: 01/10/2022
Duration (for temporary positions only): 6 months
Watch duty: NO
Travel Required: No
Weekend work: No
UK only- Watch duty – secondary: No
Reference Profile: Scrum Master, Complex
Description and what we have to offer - Internal
The Group Digital Capabilities (GDC) Division ensures competitiveness by delivering reliable and sustainable IT solutions for the financial securities markets.
Our technical teams deliver new IT solutions and improve existing applications for both our internal and external clients. We deploy changes into the production environment in a controlled and structured way that does not compromise production stability and we ensure applicative production support.
Our non-technical people maintain the maturity of the IT project delivery with appropriate controls in line with the group’s risk appetite and reducing development and running costs.
Within the GDC Division, the Data Analytics & AI chapter supports the Data Science needs of all the Group entities. As a competency centre for analytics, the team helps improve process efficiency and generate insights using techniques such as predictive modelling, natural language processing, process mining and network analytics.
- You have a proven track record of hands-on experience in the area of AI/ML/Advanced Analytics, with special focus on deploying and maintaining Machine Learning models in production.
- Keywords: EDA, model selection, tuning, evaluation, serving.
- Bonus for: NLP, OCR and text classification.
- You make sure the models you build and deploy are reproducible and interpretable.
- You have already single-handedly packaged and deployed models to production.
- You know how to monitor and update AI models post-deployment.
- You are proficient in Python
- You have 5+ years of work experience with Python, and AI/ML standard libraries such as pandas, scikit-learn, xgboost
- Nice-to-haves: FastAPI, PySpark, pydantic, pandera, NannyML, MLFlow, dagster, Airflow
- You can write OO code and understand concepts such as (de)coupling, coherence, inheritance, composition.
- You love and regularly use data validation, type hints, pytest, coverage, tox, mypy, black, flake8.
- You know how to turn a messy jupyter notebook into a production-grade piece of code.
- You know how to package a python application or library for distribution
- You are a proficient GIT user, able to collaborate with multiple developers on multiple repositories, while following best practices related to branching, merging and code reviews.
- You have experience with Unix/Linux command line tools and scripting (shell, bash):
- VIP club membership if you have at least once ran `rm -rf` on production data.
- You possess the foundational Data Engineering skills, allowing you to interact with the Data Engineering team, and analyze and troubleshoot data pipelines if needed:
- You are comfortable with using SQL to extract, transform and load data (ETL/ELT).
- Experience with the Hadoop ecosystem (Spark, Kafka, Hive, Impala…) is a plus.
- Experience with the Cloudera distribution is an additional plus
- You understand the modern MLOps framework and complexities it adds to DevOps.
- You are able to identify the MLOps maturity gaps and provide inputs for modernization efforts.
Your formal qualifications are the following:
- You have strong verbal and written communication skills as well as good customer relationship skills to present complex concepts and/or the results of a use case to different audiences (from end users up to division management).
- You have experience of working in large, complex enterprises and have stoically accepted it as your fate.
- You are not allergic to legacy technology, yet are stubborn and persistent in pushing for modernization.
- You stay up-to-date with new tools, technologies and approaches within the domain.
- You are a well-integrated team player.
- You are able to estimate your short-term effort with reasonable accuracy and get the work done in the time frame you commit to.
- You successfully swim in the waters of Agile project management techniques (scrum boards, standups, demos, reviews).
- Must love mentoring and sharing knowledge.
- Must love dad jokes.
- University degree in software engineering OR Data Science/Machine Learning/Data Engineering OR a related quantitative field, combined with strong IT skills.
- 5+ years of experience with Python
- 2+ years of experience of using DevOps/CI/CD practices.
- 2+ years of experience in deploying AI solutions to production.