Who are we? Amaris Consulting is an independent technology consulting firm providing guidance and solutions to businesses. With more than 1000 clients across the globe, we have been rolling out solutions in major projects for over a decade – this is made possible by an international team of 7,600 people spread across 5 continents and more than 60 countries. Our solutions focus on four different Business Lines: Information System & Digital, Telecom, Life Sciences and Engineering. We’re focused on building and nurturing a top talent community where all our team members can achieve their full potential. Amaris is your steppingstone to cross rivers of change, meet challenges and achieve all your projects with success.

At Amaris, we strive to provide our candidates with the best possible recruitment experience. We like to get to know our candidates, challenge them, and be able to give them proper feedback as quickly as possible. Here's what our recruitment process looks like:   

Brief Call: Our process typically begins with a brief virtual/phone conversation to get to know you! The objective? Learn about you, understand your motivations, and make sure we have the right job for you! 

Interviews (the average number of interviews is 3 - the number may vary depending on the level of seniority required for the position). During the interviews, you will meet people from our team: your line manager of course, but also other people related to your future role. We will talk in depth about you, your experience, and skills, but also about the position and what will be expected of you. Of course, you will also get to know Amaris: our culture, our roots, our teams, and your career opportunities!

Case study: Depending on the position, we may ask you to take a test. This could be a role play, a technical assessment, a problem-solving scenario, etc.   

As you know, every person is different and so is every role in a company.  That is why we have to adapt accordingly, and the process may differ slightly at times. However, please know that we always put ourselves in the candidate's shoes to ensure they have the best possible experience. 
We look forward to meeting you!

Job description

We are looking for a highly skilled and versatile Data Scientist to join our advanced analytics team. In this role, you will design, develop, and deploy recommendation systems, time series forecasting models, and machine learning solutions based on boosting and decision tree algorithms. You will work closely with cross-functional teams to turn data into actionable insights and scalable solutions.

Key Responsibilities:

Develop and optimize recommendation systems (collaborative filtering, content-based, hybrid approaches) Build and validate time series forecasting models using traditional and machine learning techniques (ARIMA, Prophet, LSTM, etc.) Implement boosting algorithms (XGBoost, LightGBM, CatBoost) and decision trees for various supervised learning tasks Collaborate with data engineers and ML engineers to deploy models on Azure and Databricks environments Perform data exploration, feature engineering, and model evaluation Present findings and models clearly to technical and non-technical stakeholders Stay up to date with the latest tools and methodologies in applied machine learning

Requirements:

Bachelor's or Master’s degree in Data Science, Computer Science, Engineering, Statistics, or a related field Proven experience with recommender systems and time series models Strong knowledge of boosting algorithms and decision trees Proficiency in Python and libraries such as scikit-learn, pandas, NumPy, statsmodels Experience with Azure cloud services and Databricks Strong problem-solving skills and ability to work independently Fluent in English (spoken and written)

 

Amaris Consulting prides itself on being an equal opportunities workplace. We are committed to promoting diversity within the workforce and creating an inclusive work environment. To this end, we welcome applications from all qualified candidates regardless of gender, sexual orientation, race, ethnicity, beliefs, age, marital status, disability or other characteristics.