Find Machine Learning Developers
We use a highly curated database to find the candidate with the skills most suited to your business’s needs. Browse the talent below, find the perfect fit and our qualified customer service agents will take care of the rest.
quant developer
- quantitative design and development for clients in financial services and manufacturing
- C++, Python, VBA
- financial mathematics, liner algebra, machine learning
- C++, Python, VBA
- financial mathematics, liner algebra, machine learning
Skills
c++
machine-learning
quantitative-developer
excel
finance
java
mathematics
matlab/simulink
python
vba
Strategist, ML engineer, data scientist and quant develope
Experienced strategist, ML engineer, data scientist and quant developer. Broad experience in IB and research.
Hands-on leader and team player. Experience in sell-side front office, mid-office, research and start-ups in both the UK and Canada.
PhD and MSc in Applied Maths (McGill), Honours BSc in Maths and Physics.
BUSINESS AND TECHNICAL SKILLS.
TECH: Machine learning, reinforcement learning, Bayesian inference, probabilistic simulation, optimization, numerical methods, data versioning and consistency, asyncio, distributed systems, databases.
BUSINESS: Credit flow, client segmentation, search/recommendation, flow/inventory management, balance sheet velocity, post-RFQ market predictions, limit-order book modelling, book imputation models, Revenue and PnL analysis for compensation adjustments, market risk, VaR, VaR backtesting, regulatory VaR models, RNIV, security and permissioning of data. • LANG: Python (TensorFlow 2.0, pandas, PyArrow, Dask, Ray, NumPy, SciPy, scikit-learn, Keras, NGBoost, XGBoost, Tornado/async, Cython), Spark, Linux, AWS (S3, Glue, Athena), Azure, internal cloud, Docker, devops, Cloudera, Spark, HashiCorp Consul, JavaScript, Git, KDB, MATLAB, SQL, C/C++, R.
Hands-on leader and team player. Experience in sell-side front office, mid-office, research and start-ups in both the UK and Canada.
PhD and MSc in Applied Maths (McGill), Honours BSc in Maths and Physics.
BUSINESS AND TECHNICAL SKILLS.
TECH: Machine learning, reinforcement learning, Bayesian inference, probabilistic simulation, optimization, numerical methods, data versioning and consistency, asyncio, distributed systems, databases.
BUSINESS: Credit flow, client segmentation, search/recommendation, flow/inventory management, balance sheet velocity, post-RFQ market predictions, limit-order book modelling, book imputation models, Revenue and PnL analysis for compensation adjustments, market risk, VaR, VaR backtesting, regulatory VaR models, RNIV, security and permissioning of data. • LANG: Python (TensorFlow 2.0, pandas, PyArrow, Dask, Ray, NumPy, SciPy, scikit-learn, Keras, NGBoost, XGBoost, Tornado/async, Cython), Spark, Linux, AWS (S3, Glue, Athena), Azure, internal cloud, Docker, devops, Cloudera, Spark, HashiCorp Consul, JavaScript, Git, KDB, MATLAB, SQL, C/C++, R.
Skills
data-scientist
machine-learning
quantitative-developer
c++
computer-science
devops
docker
finance
git
jakarta-velocity
javascript
joiner
linux
mathematics
matlab/simulink
physics
python
scala
sql
transactions-in-securities
Machine Learning Consultant
Expertise in the development of forecasting models (machine learning and stochastic predictive models)
In-depth knowledge and skills to analyze large datasets using both statistical and advanced data mining/machine learning algorithms
Analysis of large datasets from Plugged-in Midlands Project (PiM) and eBridge project related to Electric Vehicles charging events and EV trips (R studio, Matlab, SPSS, WEKA tool and RapidMiner software packages used)
Cluster Analysis using k-means algorithm to extract typical profiles (Matlab, R)
Statistical Analysis using Regression models to investigate the long-term trend of a time series (Matlab, SPSS)
Development of a quantitative risk analysis (decision making) model (based on Fuzzy-Logic) to identify the potential risk of EV charging demand on a distribution network (Matlab)
Spatial Data Analysis (using Google Earth/Google Maps, Open Street Maps)
Data Visualization experience (UML diagrams, Matlab, Microsoft Office)
Professional experience using tools and techniques to utilize Business Intelligence in order to drive competitive advantages and create new strategic business opportunities
Organizational and Analytical skills, Strong commitment to learn and a strong drive to achieve results, Intellectual skills and creative thinking, Ability to work independently and within a team environment and deal in a challenging environment under pressure, Strong independent decision-making, organizational, planning and problem-solving skills
In-depth knowledge and skills to analyze large datasets using both statistical and advanced data mining/machine learning algorithms
Analysis of large datasets from Plugged-in Midlands Project (PiM) and eBridge project related to Electric Vehicles charging events and EV trips (R studio, Matlab, SPSS, WEKA tool and RapidMiner software packages used)
Cluster Analysis using k-means algorithm to extract typical profiles (Matlab, R)
Statistical Analysis using Regression models to investigate the long-term trend of a time series (Matlab, SPSS)
Development of a quantitative risk analysis (decision making) model (based on Fuzzy-Logic) to identify the potential risk of EV charging demand on a distribution network (Matlab)
Spatial Data Analysis (using Google Earth/Google Maps, Open Street Maps)
Data Visualization experience (UML diagrams, Matlab, Microsoft Office)
Professional experience using tools and techniques to utilize Business Intelligence in order to drive competitive advantages and create new strategic business opportunities
Organizational and Analytical skills, Strong commitment to learn and a strong drive to achieve results, Intellectual skills and creative thinking, Ability to work independently and within a team environment and deal in a challenging environment under pressure, Strong independent decision-making, organizational, planning and problem-solving skills
Skills
machine-learning
machine-learning-engineer
technical-architect
bigdata
Data Scientist
I am a proactive and technologically minded professional with a strong academic record and commercial experience in data science projects for both private and public organisations. Interacting closely with C-level executives and business stakeholders, I have developed a high level of business acumen in retail, FMCG, higher education, and the healthcare sector. My adaptability, problem-solving mindset and strong communication skills, moreover, allow me to work collaboratively within multidisciplinary teams as well as cope with pressure and keep on top of deadlines effectively.
Skills
consulting
python
r
consumer-goods
retail
excel
spss
sql
Data Scientist and Machine Learning Engineer
Passionate about Technology and Businesses
Skills
deep-learning
machine-learning
mysql
python
robotics
angular
c++
computer-science
css
django
docker
finance
haskell
html/xhtml
java
javascript
model-view-controller
php
physics
postgres-sql
react
xml
zend-framework
Machine Learning Engineer / Data Science
Machine Learning Engineer / Data Science
Skills
machine-learning
python
pytorch
angular
angularjs
computer-science
css
html/xhtml
intellij-idea
javascript
numpy
pandas
postgres-sql
robotics
scikit-learn
seo/sem---search-engine-optimization-&-marketing
FAQ
What is Machine Learning?
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves
What does a Machine Learning Engineer do?
They run machine learning experiments using a programming language with machine learning libraries. They also deploy machine learning solutions into production, and optimize solutions for performance and scalability.
What is the average day rate for Machine Learning Engineers?
The average day rate ranges from £570-650 depending on experience.
What should a Machine Learning Engineer know?
Generally, machine learning engineers must be skilled in computer science and programming, mathematics and statistics, data science, deep learning, and problem solving.
