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Expert in data engineering, analysis, science and visualisation
Michael Greaves
,
Stafford, United Kingdom
Experience
Other titles
Skills
I'm offering
Over the past 20 years i have worked with VBA/VB6 as well as MatLab, R and Python. I have spent the last two years mainly working with Python and SQL providing ETL methodologies and data science support.
I have been working as a data engineer for the past 2 years implementing data pipelines to ingest, clean and process available data. I have an understanding of machine learning concepts across all areas, in particular; supervised, unsupervised and reinforcement learning. I have been providing data analysis services solving hypotheses when required to give insights into the data available. I implemented an empirical model to quantify risk to aid fleet management using machine learning techniques on time and in budget. I have always had a thirst for knowledge and always trying to keep up with new technologies and techniques.
My PhD involved utilising neural network techniques to help predict operating parameters for batch distillation processes, i have always been a great researcher and in the current climate i think being able to utilise Google efficiently is a key skill.
I also have a lot of experience in big data technologies and have excellent communication skills being able to concisely and accurately present findings to stakeholders/clients when required. I am used to working with technical and business teams and able to effectively communicate between them as required. I am able to work agile within a Scrum team environment, also have experience in Kanban. I have used version control (git) as part of agile development work streams collaboration with other data scientists. I have provided insight to stakeholders by utilising Power BI to display environmental data on maps to levels of pollution. I have a lot of experience in creating visualisations using Python.
In the past as a consultant in Oil and Gas Upstream business I thrived on troubleshooting problems for clients in areas of flow assurance, risk management and safety design. I was able to utilise which ever software best provided the solution eg transient/steady state process simulation software, multiphase pipeline transient simulation software or even Microsoft Excel.
I have been working as a data engineer for the past 2 years implementing data pipelines to ingest, clean and process available data. I have an understanding of machine learning concepts across all areas, in particular; supervised, unsupervised and reinforcement learning. I have been providing data analysis services solving hypotheses when required to give insights into the data available. I implemented an empirical model to quantify risk to aid fleet management using machine learning techniques on time and in budget. I have always had a thirst for knowledge and always trying to keep up with new technologies and techniques.
My PhD involved utilising neural network techniques to help predict operating parameters for batch distillation processes, i have always been a great researcher and in the current climate i think being able to utilise Google efficiently is a key skill.
I also have a lot of experience in big data technologies and have excellent communication skills being able to concisely and accurately present findings to stakeholders/clients when required. I am used to working with technical and business teams and able to effectively communicate between them as required. I am able to work agile within a Scrum team environment, also have experience in Kanban. I have used version control (git) as part of agile development work streams collaboration with other data scientists. I have provided insight to stakeholders by utilising Power BI to display environmental data on maps to levels of pollution. I have a lot of experience in creating visualisations using Python.
In the past as a consultant in Oil and Gas Upstream business I thrived on troubleshooting problems for clients in areas of flow assurance, risk management and safety design. I was able to utilise which ever software best provided the solution eg transient/steady state process simulation software, multiphase pipeline transient simulation software or even Microsoft Excel.
Markets
United Kingdom
Links for more
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Language
English
Fluently
Ready for
Larger project
Ongoing relation / part-time
Full time contractor
Available
My experience
2017 - 2019
freelance
Data Engineer
R2 Data Labs Civil Aerospace, Rolls-Royce Plc.
Collaborative design of ETL pipelines with other developers, managers, users
and customers whenever necessary to achieve best solution by working other
members of the development team
• Investigation of premature turbine blade failures using Data Science and Machine Learning techniques providing design guidance for data pipeline
• Investigation and prototyping of new technologies, tools and processes to deliver detailed and justified recommendations
• Full participation in Agile software development process as well as familiarity
of Scrum and Kanban methodology
• Strong experience in using different software technologies such as Python,
Linux, SQL/MySQL/Sqlite3/postgreSQL, JSON, Apache Hadoop/Spark, Jupyter,
Bash Scripting, VBA, Power BI
• Strong experience in using different python libraries such as Pandas, Numpy,
Scipy, Matplotlib, Seaborn, pyspark, NetCDF4, Pickle, itertools, JSON, Basemap,
Pyarrow, Sqlalchemy, unittest, Sci-kit learn
• Proficiency with using Git, Docker, Jenkins, Airflow, VSTF, TFS, AWS, GCP,
Azure, HTML/CSS, Requests, Urllib, Django, Flask (RESTful API's), Machine
Learning, Kafka, ActiveMQ/MQTT, Flink, Scala, Tensorflow, Keras, Tableau
and customers whenever necessary to achieve best solution by working other
members of the development team
• Investigation of premature turbine blade failures using Data Science and Machine Learning techniques providing design guidance for data pipeline
• Investigation and prototyping of new technologies, tools and processes to deliver detailed and justified recommendations
• Full participation in Agile software development process as well as familiarity
of Scrum and Kanban methodology
• Strong experience in using different software technologies such as Python,
Linux, SQL/MySQL/Sqlite3/postgreSQL, JSON, Apache Hadoop/Spark, Jupyter,
Bash Scripting, VBA, Power BI
• Strong experience in using different python libraries such as Pandas, Numpy,
Scipy, Matplotlib, Seaborn, pyspark, NetCDF4, Pickle, itertools, JSON, Basemap,
Pyarrow, Sqlalchemy, unittest, Sci-kit learn
• Proficiency with using Git, Docker, Jenkins, Airflow, VSTF, TFS, AWS, GCP,
Azure, HTML/CSS, Requests, Urllib, Django, Flask (RESTful API's), Machine
Learning, Kafka, ActiveMQ/MQTT, Flink, Scala, Tensorflow, Keras, Tableau
Flask, Scripting, ETL, VBA, Tableau, Apache, Hadoop, Kanban, Tensorflow, Bash, Scala, Spark, Django, Kafka, TFS, Restful, Keras, Development, Software, BEE, Science, Power, Processes, Blade, HTML/CSS/Javascript, Html, Design, Mysql, Sql, Python, Git, Scrum, Linux, Machine learning, API, Data Science, Css, Docker, AWS, Prototyping, Azure, PostgreSQL, JSON, Software development, Power BI, Jenkins, Agile
2006 - 2016
job
Principal Process Consultant
Performance Improvements (PI) Ltd.
Provide technical support to various clients worldwide using transient process
simulations and custom written addons using VB6
• Provided in-house and external software training
• Technical writing reports, operational procedures, oil and gas platform
manuals demonstrating good communication and presentation skills
simulations and custom written addons using VB6
• Provided in-house and external software training
• Technical writing reports, operational procedures, oil and gas platform
manuals demonstrating good communication and presentation skills
Writing, Training, Support, Software, Oil and Gas, Chemical engineer, Process Optimization, Concept Development, Engineering simulations
2004 - 2006
job
Senior Process Engineer
DNV GL.
Flow Assurance Consultancy for Oil and Gas Upstream Business
Flow Assurance, Transient Simulation, Troubleshooter, Problem solving, Process Optimization
2003 - 2004
job
Senior Support Engineer
M.W. Kellogg Ltd.
Support
2001 - 2003
job
Technical Support Engineer, Hyprotech
Aspentech Ltd.
Support
My education
1998
-
2003
University of Bradford
Doctorate, Chemical Engineering, Neural Networks, IT
Doctorate, Chemical Engineering, Neural Networks, IT
Modelling and optimisation of batch reactive distillation process was carried out using artificial neural network techniques. The proposed optimisation framework allows determination of optimal reflux ratio policies for wider product specifications and was much faster compared to existing rigorous methods. Also the method reduced the amount of computationally expensive integration of the process model equations.
A neural network based dynamic model for a Middle Vessel Batch Distillation (MVBC) process was developed based on data from a rigorous MVBC Simulator (validated previously by using experimental data). An optimisation algorithm was developed to optimise operating parameters (reflux, reboil ratios and batch time) for the MVBC process showing excellent results. The neural network based model and the optimisation framework drastically reduces computation time compared to rigorous models and optimisation methods. The effect of cost weighting on the profitability of the MVBC process was also studied.
Finally, an industrial case study of batch extractive distillation to investigate the possibility of separating a compound from a mixture of over 50 components using solvent is presented. A sensitivity analysis of the system was carried out through 25
Experiments with different parameters (reflux ratio, solvent feeding rate, heat input, initial charge) altered. Several unforeseen problems occurred during the experiments highlighting the difference between simulation and experimentally
producing results.
1994
-
1998
University of Bradford
Bachelors, Chemical Engineering with Process Control
Bachelors, Chemical Engineering with Process Control
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