Data Scientist Consultant (Central)- Remote
Austin, TX
Applications have closed
TigerGraph is a platform for advanced analytics and machine learning on connected data. TigerGraph's core technology is the only scalable graph database for the enterprise. Its proven technology supports fraud detection, customer 360, MDM, IoT, AI, and machine learning.
Fortune 500 organizations and the most innovative mid-size and startup companies choose TigerGraph to accelerate their analytics, AI, and machine learning:
- Seven out of the top ten global banks use TigerGraph for real-time fraud detection.
- Over 50 million patients receive care path recommendations to assist them on their wellness journey.
- 300 million consumers receive personalized offers with recommendation engines powered by TigerGraph.
- TigerGraph reduces power outages by optimizing the energy infrastructure for 1 billion people.
TigerGraph is leading the graph industry with its modern, graph database, analytics and ML platform and with its expansion is looking for someone to build and develop its new Customer Success team.
The Solutions Team at TigerGraph strives to continuously develop and improve the world's fastest real-time Graph Analytics platform. One key aspect of this continuous improvement is to push this high-performance engine to its limits. Members of the Solutions Team are tasked with developing cutting edge data products for real-world applications and customers using the core TigerGraph platform tools. An ideal candidate is a passionate problem solver who fearlessly approaches a customer's "impossible" problems and designs exceptional, high-performance solutions that instantly become the cutting edge in real-time data analytics applications.
Responsibilities
- Develop custom data models and algorithms to apply to graph data
- Utilize TigerGraph Machine Learning Workbench or other ML libraries to build predictive models, increase the accuracy of customer solutions
- Engage with customers’ data scientist team to demonstrate the power of graph-based ML solutions.
- Collaborate with business users to create solutions aligned with business needs
- Help drive and create reusable assets to improve the efficiency
- Documentation to aid in the understanding of the solution offerings
- Customer health checks
- Engage with pre-sales PoC/PoV to help achieve the technical win
- Contribute to a growing body of graph design and graph algorithm methodology
Key Requirements
- B.S. in related degrees with 3 years' industrial experience in machine learning or M.S. in related degrees with 1 year's experience in machine learning
- Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
- Domain knowledge of recommender system, anti-fraud, anomaly detection is a huge plus
- Linux OS and command-line experience
- Enthusiasm for graph algorithms and graph data structure design
- Ability to work independently, manage deadlines and set priorities
- Innovative entrepreneurial spirit to develop new business opportunities
- Passion for the start-up environment
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Data Analytics Industrial Linux Machine Learning Python R
Perks/benefits: Startup environment
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