Data Scientist


Job description

Our partner 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, hyperparameter 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.

• 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


• 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 - Python.
• 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 data visualization tools.
• Data-oriented personality.
• A collaborative and can-do attitude.
• Excellent story telling skills, written and verbal communication skills, comfortable with audiences including technical and non-technical ones.
• Experience in the banking industry is a plus.
• Experience in generative AI / reinforcement learning/ graph algorithms is a plus.

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