Azam Din
ML Engineer, MLOps, Leadership
Experienced ML Engineer, currently leading the MLOps team at a national supermarket bank. I’ve specialised in Python, Docker and AWS, including the Sagemaker ecosystem. I am passionate about engineering robust machine learning and data pipelines, architecting and building out cloud infrastructure, including tooling & processes for MLOps.
My current role involves being responsible for the bank’s ML platform, devveloping frameworks for contract-based ETL pipelines, ML batch inference, Data Science dev environments, CI/CD, model training pipelines and much more…
Prior to this I was a Research Data Scientist for a SaaS offering in the Sales Enablement space where I built NLP pipelines, voice feature engineering and content recommenders. As an experienced Python developer, I have mentored my teams to instill engineering quality and standardisation, especially in code quality with efforts in unit testing, abstraction layers, CI/CD.
With my MEng degree in Mechanical & Aerospace Engineering I specialised in instrumentation and data acquisition systems. I have led a wide range of analytical projects across various industries including automotive, oil & gas and IT. I am passionate about automating complex processes and building novel machine learning solutions.
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Personal projects
Energy Forecasting
Built a serverless ML pipeline for timeseries forecasting + CI/CD.
Terraform AWS Lambda sktime mlflow dvc streamlit Docker pytest github-actions
Smart Home ELT pipeline
Built an ELT pipeline to ingest smart home JSON data from Tado API, into Postgres.
airflow DockerOperator Postgres SQLAlchemy pytest JSON Makefile
Used Car Values
Web scraped auto trader adverts and predicted valuation of my own car.
python pandas numpy requests BeautifulSoup4 matplotlib seaborn sklearn
Job Description NLP
Interactive job ad classifier for data jobs. Web scraping and NLP.
requests BeautifulSoup4 pandas nltk spacy seaborn sklearn streamlit
MOT data analysis
Analysed 30mil MOT tests from GOV.uk for trends in vehicle ownership, pass/fail rates etc.
sqlite pandas seaborn sklearn
Experience
Sainsburys Bank - May/2023 to today
Led the ML-platform team (AWS, SageMaker, Terraform, CDK, Gitlab CI, Step Funcs, Lambda, CodePipeline). I led the MLOps strategy for the team, evaluating and deploying PoCs for Mlflow, Sagemaker Studio, FastAPI and Streamlit. Developed the bank's first NLP workflows including a topic modelling solution for analysing customer feedback. Built automated model evaluation pipelines. Established containerisation practises and standardised the team's python dev tooling (poetry, ruff, pre-commit, Gitlab CI, cookiecutter templating). Developed a self-service ETL framework for deploying pipelines using JSON contracts (Python, CDK and AWS Step Functions).
Bigtincan, Sales Enablement - Jan/2022 to Apr/2023
I primarily worked on NLP pipelines, text classification, online topic-modelling, embeddings, voice analytics. I built and deployed an interactive sales call analytics system using EC2, Docker & spaCy. With my engineering focus I established standardised MLOps tooling like Mlflow and DVC, managed a Prodigy annotation server and was responsible for data engineering and ingestion workflows.
Doosan Babcock - May/2019 to Dec/2021
I served in a technical consultancy as the lead engineer and client-facing project manager for a €1.6 million test-engineering contract. I reported to both client and senior management and explained technical topics to a diverse audience. I used pandas to build a data extraction pipeline and automated visualisation and report generation, doubling documentation throughput. I established the team's Git version control and authored 20+ technical reports.
Jaguar Land Rover - Apr/2017 to Apr/2019
As an analyst, I presented competitor and market intelligence to Directors and built forecasts for early electric vehicle adoption. I proposed and developed a new EV fleet telematics data pipeline and created a regression model to predict EV battery failures, which helped the business to assess a potential warranty risk of over £10 million. I was also the lead engineer in a technology partnership that delivered a prototype robotic EV charger.
Jaguar Land Rover - Sep/2015 to Mar/2017
I was responsible for conducting **objective** testing and subjective assessment, as well as developing data processing automation tooling and data validation tools using MATLAB. I also developed new vehicle assessment metrics and supported CAE-based tuning using a driving simulator.
Skills
| Languages & Technologies | Python SQL Docker Devcontainers AWS Sagemaker GCP Databricks Terraform Linux Git Bash Jupyter Matlab CI/CD |
| Python libraries | sklearn tensorFlow pytorch mlflow dvc wandb airflow matplotlib plotly seaborn scipy pandas numpy sktime spaCy Prodigy nltk librosa dask pyspark transformers BERTopic pre-commit BeautifulSoup4 |