Machine Learning Scientist
We believe that properly collected and analyzed data is inherently honest buy often businesses only have access to narrow slices of data about their customers or audiences, or the data they have looks only at what people say and not what they do.
That’s why Helixa has developed technology to look at groups of people, from every angle and dimension, and delivers a way to get more insight into both their hearts (behavior, interests, beliefs) and minds (stated intentions) than you’ve ever had.
We have infused our AI with the most current research into human behavior and given it access to the latest demographic, engagement, and census data to enable truly representative, uniquely insightful, deeply human results. AI offers the ability to find patterns and connections at unparalleled depth, scale, and speed, providing insight in minutes not days. With a detailed understanding of your customers or audience, you will be better able to please them, move them, and build more profitable relationships… everyone wins.
The AI team at Helixa is at the forefront of innovation in advanced analytics and machine learning, including deep learning and more traditional algorithms.
Our team is composed by top class scientists, engineers and domain experts driving the data science capabilities of our products end-to-end, including: data ingestion and processing, exploratory analysis, modeling, validation, visualization, tuning and automation.
We alternate the development workflow with research spikes on state-of-the-art machine intelligence applied to understanding and generalizing people behaviour and affinities.
Our R&D strives to cover a full spectrum of topics: probabilistic programming, cross-domain adaptation, natural language processing, computer vision, generative models, scalable distributed systems and GPUs hardware optimizations just to name few.
Artificial Intelligence at Helixa raises both scientific and engineering challenges. We deal with a very large amount of data and rely on various data management and distributed computing technologies (Spark, MongoDB) deployed into cloud infrastructures (AWS). We utilize a diverse number of languages (Python, Scala) and tools (PyData stack, MLlib, TensorFlow, Keras, PyTorch). Periodically, we work side by side with the core development team for maintaining the data lake and for deploying solutions in production with the minimum overhead.
The ultimate goal is to help the company growing on three major areas:
- Understanding consumer characteristics, preferences and lifestyle.
- Predicting latent variables and future outcomes (e.g. hidden traits, migrations, market indicators).
- Augment with unobserved patterns (e.g. generate synthetic consumers population, latent factors fusion, personalizations).
In addition to the core business, 10% of team time on a weekly basis is devoted to learning and experimenting with latest advances in Artificial Intelligence, Deep Learning, Sociology and Data Technologies.
A Machine Learning Scientist at Helixa focuses on researching and developing new algorithms, exploring new hypothesis, running experiments, validating models and yielding insights. Besides that, our scientists and engineers work as a team and are responsible for the whole end-to-end process, from research to production. Besides that, our scientists and engineers work as a team and are responsible for the whole end-to-end process, from research to production.
This role in particularly will lead to a great impact in building predictive models for estimating categorical variables of consumers, unsupervised algorithms for extracting latent characteristics and hidden patterns in the consumer affinities and lifestyles, modeling feature embeddings of contents and entities in our datasets.
The ideal candidate is an experienced professional with a blend of coding, machine learning and business acumen.
The position is based in our rapidly growing R&D office in Milan (Italy) @ Talent Garden Merano.
- Carry out projects involving data pipelines, statistical models and machine learning algorithms.
- Explore and analyze multi-dimensional data in order to find patterns and relationships.
- Develop intelligent systems based on the latest AI technologies and deep learning.
- Be expected to be analytical, accurate but also creative and to come up with your own ideas and suggestions.
- Research and implement novel approaches to add value to the business.
- Contribute to the state of the art by publishing articles or contributions to the open source community.
- Work closely with the Chief Scientist and Product Owner to design new features to implement to improve the functionalities and user experience of the platform.
- Work closely to the marketing and sales teams to find solutions and products that help lead generation and inbound marketing.
- Work closely to the core development team in order to integrate the AI technology into our platform and future products.
- Adopt a Continuous Learning process in order to be always up to date with the latest and more productive technologies.
- Master’s degree or above in STEM fields (science, technology, engineering or mathematics) or a similarly quantitative field.
- 2 years+ experience, or a comparable industry career, in Machine Learning, Deep Learning, Computer Vision, NLP, Pattern Recognition or similar.
- Working knowledge of Python and the PyData stack or other numerical programming languages.
- A scientific mentality with the ability to ask the right questions, as well as answer them.
- Ability to convey complex analyses with the most efficient and intuitive visual interactions.
- Ability to break research down into clearly defined tasks and quick iterations.
- PhD with a proven track record of publications in Statistics, Data Science, Computer Science, Machine Learning, Mathematics or similar.
- Experience with large volume data analysis.
- Knowledge of deep learning techniques for recommender systems, NLP, auto-encoders or generative models.
- Knowledge of parallel computing using GPUs and CUDA.
- Familiar with agile development and lean principles.
- Contributor or owner of GitHub repo
- Competitive salary.
- Stock options.
- Free lunch delivered daily.
- Personal budget for conferences and training.
- Flexible working hours.
- Startup atmosphere with the usual perks.
- Regular team building activities.