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0
jobs
Data Science Contractor
Ioannis Melas
,
Cambridge, United Kingdom
Experience
Other titles
Skills
I'm offering
- Prototype, develop and deploy Data Science and Machine Learning (MLDS) workflows to best
leverage the business’s data and enable data driven decision making.
- Develop/implement machine learning and computational statistics methods in Python and R to: (i) interpret
complex datasets e.g. dimensionality reduction, feature extraction, model fit/parameter
estimation (unsupervised analysis), and (ii) address classification/regression problems
(supervised analysis).
- Experience in all major data types: Structured data, Free text – Natural Language Processing
(NLP), Time series analysis.
- Experience in most major ML algorithms including Deep Learning, Random Forests, Gradient Boosting algorithms, etc.
- Mathematical modeling and parameter estimation of complex systems using Linear/Non-Linear Programming formulations.
- Experience with SQL, Elasticsearch
- Deploying applications in the Google cloud.
leverage the business’s data and enable data driven decision making.
- Develop/implement machine learning and computational statistics methods in Python and R to: (i) interpret
complex datasets e.g. dimensionality reduction, feature extraction, model fit/parameter
estimation (unsupervised analysis), and (ii) address classification/regression problems
(supervised analysis).
- Experience in all major data types: Structured data, Free text – Natural Language Processing
(NLP), Time series analysis.
- Experience in most major ML algorithms including Deep Learning, Random Forests, Gradient Boosting algorithms, etc.
- Mathematical modeling and parameter estimation of complex systems using Linear/Non-Linear Programming formulations.
- Experience with SQL, Elasticsearch
- Deploying applications in the Google cloud.
Markets
United Kingdom
(Remote
only)
Links for more
Once you have created a company account and a job, you can access the profiles links.
Industries
Language
English
Fluently
Ready for
Larger project
Ongoing relation / part-time
Full time contractor
Available
My experience
2019 - ?
freelance
Data Science Contractor
ARM Holdings.
UK
Role: Develop a Machine Learning/Data Science (MLDS) workflow for optimal
design of stimuli/payloads for CPU/GPU verification. Project lead and principal
developer. MLDS parts were developed using Keras/TensorFlow implemented in Python, stitched together using Shell scripting and deployed using Jenkins.
Integrated work from 3 other developers. All development took place within Git.
Role: Develop a Machine Learning/Data Science (MLDS) workflow for optimal
design of stimuli/payloads for CPU/GPU verification. Project lead and principal
developer. MLDS parts were developed using Keras/TensorFlow implemented in Python, stitched together using Shell scripting and deployed using Jenkins.
Integrated work from 3 other developers. All development took place within Git.
Design, Python, Git, Machine learning, Data Science, Jenkins, Scripting, Tensorflow, Workflow, Developer, Keras, Science, Development
2019 - 2019
freelance
Data Science Contractor
Mango Solutions.
UK
Role: Senior Data Science Consultant, client facing, working across industries in
a commercial and fast paced environment. Agile development (CI/CD) of
analytical/ML tools and methods. Use of R and Python to analyze and interpret
complex datasets and deploy in production. Experience with the GCP and IBM
cloud.
Role: Senior Data Science Consultant, client facing, working across industries in
a commercial and fast paced environment. Agile development (CI/CD) of
analytical/ML tools and methods. Use of R and Python to analyze and interpret
complex datasets and deploy in production. Experience with the GCP and IBM
cloud.
Python, Data Science, Agile, Agile development, R, Cloud, Science, Development, Production, CI / CD, CI / CD, CI / CD
2016 - 2019
job
Principal Scientist
UCB Celltech.
UK
Role: Methods development for the interpretation of complex datasets in drug
discovery/development and enablement of decision making. Leading a small
team and project leadership.
In more detail: (i) Use of R and Python for data wrangling e.g. pandas, dplyr,
tidyr for merging, pivoting/spreading, melting/gathering, etc., data into
DataFrames. (ii) Exploratory analysis to visualize and interpret complex datasets and generate hypotheses, e.g. dimensionality reduction for visualization via
PCA, T-sne, self organizing maps, stacked auto-encoders using numpy, scipy,
scikit-learn, h2o, keras; clustering e.g. hierarchical clustering, k-means etc.;
construction of correlation/similarity networks and network modeling (e.g. community detection, topological graph analysis using igraph) (iii) computational
statistics for hypothesis testing (e.g. t-test, fisher-tests, chi-squared test etc.)
(iv) machine learning for classification/regression in R and Python, e.g. mlr,
randomForest, cluster, h2o etc. packages in R, and scikit-learn, keras in Python.
(v) construction of Bayesian networks in R using bnlearn. (vi) interactive
visualization in R shiny and spotfire.
Role: Methods development for the interpretation of complex datasets in drug
discovery/development and enablement of decision making. Leading a small
team and project leadership.
In more detail: (i) Use of R and Python for data wrangling e.g. pandas, dplyr,
tidyr for merging, pivoting/spreading, melting/gathering, etc., data into
DataFrames. (ii) Exploratory analysis to visualize and interpret complex datasets and generate hypotheses, e.g. dimensionality reduction for visualization via
PCA, T-sne, self organizing maps, stacked auto-encoders using numpy, scipy,
scikit-learn, h2o, keras; clustering e.g. hierarchical clustering, k-means etc.;
construction of correlation/similarity networks and network modeling (e.g. community detection, topological graph analysis using igraph) (iii) computational
statistics for hypothesis testing (e.g. t-test, fisher-tests, chi-squared test etc.)
(iv) machine learning for classification/regression in R and Python, e.g. mlr,
randomForest, cluster, h2o etc. packages in R, and scikit-learn, keras in Python.
(v) construction of Bayesian networks in R using bnlearn. (vi) interactive
visualization in R shiny and spotfire.
Python, Machine learning, R, Leadership, Test, Statistics, Network, Keras, Community, Testing, Development, Visualization, Detail, Spotfire
2015 - 2016
job
Senior Scientist
AstraZeneca.
Sweden
Role: Analysis and interpretation of large-scale datasets to identify patterns/
connections/ co-regulations and facilitate decision making in drug development.
Application of machine learning and computational statistics algorthims in R,
python and matlab.
In more detail: Data wrangling in R and Python; Exploratory analysis like PCA,
T-sne, clustering, construction of correlation networks to identify structure and
patterns in complex datasets (implemented in R and Python). Emphasis in the implementation of statistical tests to distinguish statistically significant
relationships/associations in high dimensional datasets from noise. For example
random sampling/bootstrapping to identify underlying distributions in the data,
comparison with null distributions etc.
Role: Analysis and interpretation of large-scale datasets to identify patterns/
connections/ co-regulations and facilitate decision making in drug development.
Application of machine learning and computational statistics algorthims in R,
python and matlab.
In more detail: Data wrangling in R and Python; Exploratory analysis like PCA,
T-sne, clustering, construction of correlation networks to identify structure and
patterns in complex datasets (implemented in R and Python). Emphasis in the implementation of statistical tests to distinguish statistically significant
relationships/associations in high dimensional datasets from noise. For example
random sampling/bootstrapping to identify underlying distributions in the data,
comparison with null distributions etc.
Python, Machine learning, Matlab, R, Statistics, Implementation, Development, Detail, Patterns
2014 - 2015
job
Post Doctoral Fellow
U.S. Food and Drug Administration.
USA
Role: Analysis/processing of genomic data to predict drug toxicity. Developed and published linear programming algorithm in python.
In more detail: Developing parameter estimation methods based on Regular
Optimization formulations (e.g. ILP, MIP, NLP) using CPLEX and Gurobi in Python to model the dynamics of complex networks. Use these models within a
classification framework to predict adverse events of experimental drugs (implemented in Python).
Role: Analysis/processing of genomic data to predict drug toxicity. Developed and published linear programming algorithm in python.
In more detail: Developing parameter estimation methods based on Regular
Optimization formulations (e.g. ILP, MIP, NLP) using CPLEX and Gurobi in Python to model the dynamics of complex networks. Use these models within a
classification framework to predict adverse events of experimental drugs (implemented in Python).
Python, NLP, Detail, Processing, USA, Framework
2013 - 2014
job
Post Doctoral Fellow
European Bioinformatics Institute.
UK
Role: Analysis of genomic data to construct information networks predictive of drug efficacy in cancer. (R and python).
In more detail: Developing regular optimization algorithms to model complex
signaling networks and fit them to experimental data. Data wrangling in R, ILP
implementation in Python.
Role: Analysis of genomic data to construct information networks predictive of drug efficacy in cancer. (R and python).
In more detail: Developing regular optimization algorithms to model complex
signaling networks and fit them to experimental data. Data wrangling in R, ILP
implementation in Python.
Python, R, Algorithms, Implementation, Detail
2012 - 2014
job
Research scientist
ProtATonce Ltd.
Greece
Role: Developed computational pipelines in R for processing proteomics data and print html reports using markdown.
Role: Developed computational pipelines in R for processing proteomics data and print html reports using markdown.
Html, HTML/CSS/Javascript, Research, R, Print, Processing
2012 - 2012
temp
Visiting Student
Max Planck Institute.
Germany
2011 - 2011
job
construction of networks capturing information flow in the cells. (in C)
Massachusetts Institute of Technology.
Visiting Student
& 5/2012 - 8/2012 Massachusetts Institute of Technology (MIT)
Biological Engineering Department
& 5/2012 - 8/2012 Massachusetts Institute of Technology (MIT)
Biological Engineering Department
C, Technology, Engineering
My education
2009
-
2013
National Technical University of Athens
Dr. Eng., Bioinformatics, Numerical Optimization, Machine Learning
Dr. Eng., Bioinformatics, Numerical Optimization, Machine Learning
2003
-
2008
National Technical University of Athens
Masters in Engineering, Mechanical Engineering
Masters in Engineering, Mechanical Engineering
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