Senior Data Scientist
As a Senior Data Scientist, you have extensive experience with generative and discriminative classification and regression, linear and non-linear dimensionality reduction, predictive analytics and time series modeling. You will be part of our Data Science Team and you are passionate about machine learning and data analysis.
- You will design and implement state-of-the-art methods for both supervised and unsupervised learning.
- You will work with big data (GPS fixes and sensors) from hundreds of thousands of users.
- You will train algorithms to predict low events concepts (type of transports, home/work location) and human behavior (commuting, sporting, shopping).
- You will help the team to improve upon current methods and models. With a practical mindset you will bring these models into a production environment.
- Your software development experience will allow you to closely collaborate with our Data Engineering team to improve our models and push them through our release process.
Desired skills and expertise
- You have a masters degree or PhD in computer science or a related field.
- You are an expert in machine learning and data modeling.
- You have proven experience with generative (e.g. Gaussian Mixture Models) and discriminative (e.g. Random Forest) classification techniques.
- You possess a deep understanding of clustering, manifold learning and predictive modeling techniques.
- You have a strong mathematical background and analytical mindset.
- You are fluent in English.
- You can work independently and take matters into your own hands.
- You have software development experience in Python.
- The ability to quickly learn new technologies and successfully implement them is a true strength of yours.
We have 2 open Sr. Data Scientist positions, each with its specific focus:
Sr. Data Scientist Mobility Sensing - Experience with any of the following is desired:
- Signal Processing: pre-processing, Band-pass filtering, downsampling with anti-aliasing, Fourier/Cepstrum analysis
- Temporal Modeling: HMMs, Dynamic Bayesian Networks, Kalman and Particle Filtering
Sr. Data Scientist Lifestyles Interpretation - Experience with any of the following is considered a plus:
- Geo-spatial and Spatio-temporal learning
- Representation Learning
- Natural Language Processing; Word2Vec, Doc2Vec, POS Tagging
- Graph and/or Sequence Modeling and Mining; Node2Vec, Random Walks
- Deep Learning; LSTMs, Convolutional neural networks, etc.
- Sensor data modeling from mobile devices or wearables
- Data engineering expertise
- Experience with Java