Director of data science and ml

Perfil buscado (Hombre/Mujer)


The Director of Data Science and Machine Learning will have tho following responsibilities:

Responsibilities
• Oversee and deliver technical data science projects. This will include:
• Business/Product problem definition
• Data Strategy (Sourcing/Structure/Hosting)
• Collaboration with Data Engineering to build/deploy pipelines
• Algorithm Selection / Methodology testing
• Engineering solutions to a production code level & MLOps oversight
• Communicating these projects to clients/stakeholders in a way that delivers maximum impact against objectives

• Direct line manager of 4-6 Data Scientists
• Collaborate with product team to scope and land projects & product features
• Act as a subject matter expert in the field of Data Science & Machine Learning
• Be/Become an expert on the intersection between data science and PR/Communications
• Collaborate with experts, including psychometricians, behavioural scientists, data engineers, and digital/marketing professionals to scope, pitch, land and deliver projects
• Significantly contribute to innovation and R&D across the company

• Multinational Company (Data-Driven)|MLOps, NLP, Director of Data Scientist and Machine Learning

The Director of Data Science and Machine Learning will be someone who has experience in a multitude of machine learning areas and can collaborate with other specialisms and dev teams to create impactful outputs for the comany and clients.

Someone who is technically skilled, focussing on the oversight and delivery of high quality outputs from the team but who can also collaborate and scope with business partners and product teams.

Technical Requirements
• Bachelors/Masters Degree in Machine Learning, Mathematics, Statistics or Computer Science
• Extensive Applied Machine Learning Experience, Including but not limited to:
• Supervised Learning Algorithms: Regressors (Logit, Linear, Lasso, Ridge, GLMs), Tree Based (XGBoost, LightGBM, RF), SVMs, Naïve Bayes, Neighbour algorithms, Ensemble techniques.
• Clustering: Hierarchical/RFM/Kmeans/HDBScan
• Factorization Approached (NMF/Factorization machines)

• Deep Learning Experience, Including some of but not limited to:
• Neural Networks (Multi-Layer-Perceptrons, Autoencoders, CNN´s, RNN´s, LSTM´s)
• Generative Algorithms
• Proficient in at least one deep learning framework (Pytorch, Tensorflow, MXNet)
• Transfer Learning

• NLP Experience, Including some of but not limited to:
• Vectorization approaches
• Probabilistic models
• Deep Learning Language Models
• Transformer Models

• 6+ Years Machine Learning Pipeline Development
• Production Level Python
• Extensive experience in cloud based deployment frameworks (AWS or GCP based)
• Strong Data Engineering experience: Enterprise databases, datalakes, data pipelines, apache Spark
• Extensive MLOps implementation experience

Non Technical Requirements
• 6+ years experience of applying Data Science to commercial problems
• Proven track record of delivering high impact projects for clients using data science
• Team Leadership Experience
• Strong Communication skills of converting technical concepts to business solutions
• Selling in and landing data science projects to clients
• Innovative and collaborative
• Strong project management skills of technical projects
• Experience in client facing roles, ideally in the communications space

Multinational company specialised in Data Science projects

Interesting professional opportunity.

The Director of Data Science and Machine Learning will belong to a global Product group with the remit of building ML powered software applications. This person will play a pivotal role in landing and delivering the machine learning innovations and developments that power our products.

Remote/Hybrid model