What you will do
- Work closely with the head of data science, head of analytics strategy and, potentially vendors, to identify analytics opportunities based on a deep understanding of AFG businesses and their information assets.
- Lead the delivery of use cases by proposing and delivering advanced analytic models, utilizing a blend of contemporary and traditional data mining techniques, applied to both structured and unstructured data sets.
- This includes, conducting data quality assessments, sharing relevant insights with business stakeholders, creating model monitoring solutions and conducting QA on other data science models (built internally or through 3rd party vendors).
- Implement models by transforming/optimizing for performance code and deploying them into production.
- Provide guidance, training and coaching to junior data scientists and the analytics community on data science frameworks, best practices, and technologies.
- Support in the development of analytics standards and protocols to ensure scalability and support self-service advanced analytics.
- Research and stay up to date on latest data science and analytics approaches and practices in the market ensuring that, when relevant, these are appropriately leveraged within Data and Analytics function
Required Skills to be successful
- Proven track record of shipping machine learning-powered algorithm products at B2C-like scale as well as working with cross-functional teams in an agile-like environment.
- “Design and prototype” part of the ML development pipeline, beginning with pulling datasets from SQL and ending with serializing ML models and assisting engineers to productionize model retraining and model serving systems.
- Practical experience of running impactful inferential analyses and data investigations to identify recurring patterns, root causes, and propose actionable product solutions.
- Design approaches to validate findings or test hypotheses, interpret experiments to measure the impact of new features.
- Have no problem communicating with ML/algorithm designs clearly to cross functional team members, especially engineers and product managers.
- Excellent organizational, multi-tasking, and time-management skills
What equips you for the role
- 7+ years of working experience in data science, with at least 3 years working in developing and deployment ML/DL solutions focused on batch and real-time data pipelines.
- Master’s degree in Statistics, Machine Learning, Mathematics, Economics, Computer Science, Engineering, or any other related quantitative field. Proven record of delivering business impact through analytics solutions.
- Highly proficient and experienced in scripting languages and have rapid prototyping skills, that is, fluency in SQL, Python, Spark, etc. among others.
- Experience on the Azure Cloud platform: including Azure Databricks, Azure ML, Azure IoT etc.
- Experience working with Developer tools such as Azure DevOps, PyCharm/MS Visual Studio, Docker etc. Well versed in CI/CD and MLOps.
- Experience with probability and statistics inclusive of machine learning, optimization, forecasting and experimental design.
- Deep understanding of machine learning & deep learning concepts and algorithms, various statistical techniques, and experimentation analysis workflows.
- Experience in benchmarking and model performance evaluation and improvement.