![Kontakt](https://media.trabajo.org/img/noimg.jpg)
Senior Data Scientist
3 weeks ago
About
- is the industry leader in indoor environmental, location and occupancy services using Bluetooth Low Energy (BLE ). Our mission is to deliver human-building interfaces that provide people with delightful, useful, and safe indoor experiences to help make buildings work for people. We are out to define a new building DNA that is human-centric. We build technologies that help transform buildings into indoor spaces that are useful for people in their daily journey to accomplish their goals, working or being cared for in a safe & sustainable indoor environment._
- We started in 2013 when _
- Kontakt.io_
In an increasingly connected world, massive amounts of structured and unstructured data open up new opportunities, in we are building the AI Team to accelerate our initiatives by providing a
novel system to estimate individual proximity via a joint model of BLE signals with other on-device sensors.
We are looking for
Senior Data Scientist to turn complex data sets into useful information and solve global challenges.
We are looking for someone who works best in a fast-paced environment, desires growth, take risks on bold ideas, and is open to learning from other world-class engineers.
We are looking for someone who is continuously looking forward to using their knowledge to solve complex business problems, has an unstoppable thirst for knowledge, and is comfortable with ongoing skills development, whether it comes to learning completely new technology or mastering relevant ML algorithms.
Your daily work will include:
- Modeling RSSI-BLE Signals for digital asset tracking and contact tracing
- Interpreting the sensor data stream (time series, histogram, etc.) and using several statistical and deep learning methods to learn representations for sensing proximity
- Analyzing the differential impact of the various input signals
- Experimenting with level metadata (such as device models, power, signal strength, etc.)
- Using machine learning and cloud technologies to enable data science capabilities at scale
Job requirements:
- University degree in Computer Science, Mathematics, Statistics, Informatics, Artificial Intelligence, Physics or a similar field
- At least
23 years of practical experience within the industry or consulting in a statistical and/or data science role, preferably in a cloud environment - Experience in coding in
Python: - Understanding various Data Science and Machine Learning concepts and algorithms such as clustering, regression, classification, forecasting, neural networks, hyperparameters optimisation etc.
- Modelling stochastic realtime data series
- Outlier and anomaly detection
- Datadriven storytelling and visualisation skills (with tools like Apache Superset, Tableau, QuickSight, etc.)
- Customer and resultoriented personality, convincing with creative approaches
- Startup mindset
- Ability to work autonomously to deliver complex projects
Virtues and Culture
Lead customer-centric - customer leadership is the key. If a customer has a problem we don't wait. We understand what customer needs and we tailor our services, products around the customer. It doesn't mean that we let the customer lead us. It means that we think about the customer first
Have a growth mindset - we commit to results and growth. We are responsible for results, not for the activity or time spent. If we believe we can't achieve a result or a job, it's our duty to raise the voice, push back, explain what we suggest instead. We don't see results as something static - ever. This means that our results and expectations are becoming more ambitious, quarter over quarter. We constantly evolve
Challenge, inspire, respect:
- we are the challenger in the marketplace. When working with each other - or with customers - we enjoy and desire to challenge each other. We listen, reflect, and respond. We aim to understand the point of view of the other party and if there is customer merit in the argument. When we challenge, we articulate our hypothesis clearly and provide data and evidence in our argumentation. We respect the time of our colleagues. We have a zero-tolerance towards discrimination of any kind. We respect the environment
Execute systematically - We recognize that the start-up journey will only be successful if we learn twice as much as others in half the time. For us, innovation also means continuous improvement in all fields. We think in systems when driving results, growth, and learni
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