Coinalytics Co.: Sr. Machine Learning Engineer / Data Scientist
Our path-breaking platform brings real-time machine learning and graph analytics capabilities to the blockchain, and pragmatic and data-driven solutions to the worlds of payments, financial services and the Internet of Things.
Company: Coinalytics Co.Location: Palo Alto, CA
Web: www.coinalytics.co
_Contact_:
Apply at: join@coinalytics.co
Contact: founders@coinalytics.co
Driven by the vision of decoding the world's most powerful dataset, Coinalytics has developed an end-to-end intelligence platform, where we combine a variety of datasets and analytics to provide actionable insights and operational intelligence to the Bitcoin industry.
Our path-breaking platform brings real-time machine learning and graph analytics capabilities to the blockchain. Coinalytics provides pragmatic and data-driven solutions to the worlds of payments, financial services and the Internet of Things.
Founded in April 2014, we are a well-funded team of engineers and analytics specialists who build, run, and deploy customer-facing data solutions on large scale distributed computing platforms, headquartered in Palo Alto, CA.
What you'll do
- Provide solutions and collaborate with data experts, customer-facing staff, plus in-house and external engineering teams.
- Develop machine learning and graph algorithms on a distributed scalable computing platform.
- Apply machine learning and graph analytic solutions to the blockchain domain at production scale.
Requirements
- Masters Degree, Ph.D. preferred, in Computer Science (or closely related) with an emphasis in Machine Learning, Artificial Intelligence and Graph Algorithms.
- Comfortable analyzing complex, high volume, multi-dimensional data to drive actionable decisions in real-time.
- Capable of providing insights, predictions and recommendations from unstructured, structured, and streaming data sets.
- Programming experience in Scala, Python or comparable language.
- Familiarity with graph theory and experience developing graph algorithms.
- Experience with a wide range of machine learning techniques including supervised, unsupervised and semi-supervised learning.
- Experience with a wide range of graph analytic techniques including methods of clustering, ranking, traversal and determining centrality.
- Demonstrated expertise implementing applied machine learning (e.g., classification, optimization, prediction) and graph analytic (e.g., shortest path, knowledge discovery) solutions to interesting use cases.
Is a Plus
- A thorough understanding of the blockchain data model.
- Experience in deep learning.
- Experience with R, MATLAB or comparable language.
- Experience conducting performance modeling, memory optimization and optimizing space/time tradeoff decisions in high-performance distributed computing technology platforms.
- Expertise in data visualization techniques.
What we offer
- Become member of an early-stage startup and own your projects.
- Work on exciting big data challenges using cutting-edge technologies.
- Competitive compensation and benefits.
- Generous equity package in an early-stage startup.
