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Senior Data Scientist

Lisboa

Descrição da posição

One of our clients in the banking industry is looking for a data scientist to integrate the Artificial Intelligence Platform area. Your primary focus will be in applying data mining techniques and statistical analysis to a whole range of projects, dealing with all aspects of the machine learning lifecycle, encompassing preprocessing, feature extraction, training, hyper parameter tuning, scoring, etc. You will also help develop end-to-end machine learning pipelines, from data collection strategies to inference services deployments, building AI/ML frameworks and solutions at scale.

This is a 100% remote opportunity, however, we emphasize that it is essential for the candidate to be physically located in Continental Portugal

Responsibilities

Explore, test and find the best algorithmic solutions to the problems at hand
Help building frameworks that reuse technical solutions to known problems, while also promoting solution sharing among projects/departments.
Evangelize the adoption of frameworks that accelerate the solution of machine learning problems at scale
Selecting features, building and optimizing classifiers using machine learning techniques
Data mining using state-of-the-art methods
Enhancing data collection procedures to include information that is relevant for building analytic systems
Processing, cleansing, and verifying the integrity of data used for analysis
Doing ad-hoc analysis and presenting results in a clear manner
Be part of the creation of machine learning pipelines, referencing strategies from data collection to inference services building and deployment

Requirements

Excellent understanding of machine learning techniques and deep learning algorithms (such as k-NN, Naive Bayes, SVM, Random Forests, MLP, LSTM, etc.) and libraries (such as pandas, numpy, tensorFlow and Scikit-Learn).
Experience with common data science toolkits, such as Python or R. Excellence in at least one of these is highly desirable
Good applied statistics skills, such as distributions, statistical testing, regression, etc.
Very good scripting and programming skills
Experience in Apache Spark, Databricks, and distributed training
Proficiency in using query languages such as SQL, Spark SQL, etc.
Experience with NoSQL databases, such as MongoDB, CosmosDB, etc.
Familiarized with container technologies like Docker and Kubernetes
Experience with data visualization tools
Data-oriented personality
Data Analyst with Proven Expertise in Graph Theory Applications for Business Optimization, as well as Experience in Reinforcement Learning, LLM, and Prompt Engineering
Experience in generative AI / reinforcement learning/ graph algorithms
Experience in neural networks and monitoring of models deployed in production

Valued:

Experience in the banking industry is a plus.
A collaborative and can-do attitude
Excellent story telling skills, written and verbal communication skills, comfortable with audiences including technical and non-technical ones.
Fluency in English

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