Applied Data Scientist (M04213)
Applied Data Scientist
About the role
Airudi is looking for an applied data scientist to discover the information hidden in vast amounts of data, and to build the AI models that will enable Human Resources professionals to make smarter decisions.
Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our cloud native solutions.
This is a position for a hands-on data scientist that offers you the opportunity to work with data and software practitioners on the one hand and with academic researchers on the other hand. You’ll be part of a diverse, multi-disciplinary team including software and machine learning developers, HR specialists, designers, data scientists and AI researchers.
- Selecting features, building and optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Extending Airudi’s data with third party sources of information when needed
- 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
- Creating automated anomaly detection systems and constant tracking of its performance
- Collaborate with business subject matter experts, technical professionals and academic researchers
- Maintain state-of-the-art data science experience through continuous learning and share knowledge within the team
- Provide and promote data science excellence to support multiple initiatives in parallel
Skills and qualifications
- At least 5 years of industry work experience or university experience with a strong focus on application
- Excellent understanding of machine learning techniques and algorithms, such as deep learning, k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Strong practical experience with Python and relevant data science and machine learning libraries, such as Tensorflow, NumPy, etc
- Great communication and presentation skills
- Willingness to gradually acquire relevant HR domain knowledge
- Experience with data visualization tools
- Experience with SQL and NoSQL databases, such as Ms SQL, MongoDB, Cassandra, Hbase
- Good applied statistics skills, such as distributions, statistical testing, regression, etc.
- Functional in a remote work environment
- Inspiring leader, data-oriented, continuous learner, critical thinker, self-motivated, team-player, effective communicator
- Graduate degree in a quantitative discipline (Mathematics, Statistics, Computer Science, Engineering, Physics, Economics, etc)
- Bilingual (French/English) is a strong asset
- PhD in a quantitative discipline
- Publication record of applied data science / machine learning papers
- Experience with Natural Language Processing
- Experience with conversational AI
- Experience with Operations Research
- Software engineering expertise
- Experience with machine learning pipelines on Microsoft Azure