Senior Pre-sales Data Scientist
il y a 2 semaines
**Our Company**
Teradata is the connected multi-cloud data platform for enterprise analytics. Our enterprise analytics solve business challenges from start to scale. Only Teradata gives you the flexibility to handle the massive and mixed data workloads of the future, today.
The Teradata Vantage architecture is cloud native, delivered as-a-service, and built on an open ecosystem. These design features make Vantage the ideal platform to optimize price performance in a multi-cloud environment.
**What You’ll Do**:
**Who You’ll Work With**:
- Provide pre-sales support at an executive level to the Teradata account teams, helping to position and sell complex analytic solutions that drive sales of Teradata software.
- Offer strategic pre-sales consulting to executives and senior managers in target markets.
- Support the delivery of PoC and PoV projects demonstrating the viability and applicability of analytic use-cases and the superiority of Teradata solutions.
- Work with the extended account team and Sales Analytics Specialists to develop new analytic propositions aligned with industry trends and customer needs.
- Proven hands-on experience with complex analytics at scale, such as IoT and sensor data.
- Understanding of PMML and ONNX model portability standards.
- Experience with Teradata partner analytical products, cloud services like AzureML and Sagemaker, and partner products such as Dataiku and H2O.
- Strong programming skills in at least one major analytic language or tool, in addition to SQL.
**What You’ll Bring**:
- Expertise in Data Science with a solid foundation in statistics, advanced analytics, and machine learning, plus at least 5 years of real-world experience.
- A passion for knowledge sharing and ongoing professional development.
- A belief in Teradata's analytic solutions, with a commitment to collaborating with product, engineering, and consulting teams to maintain market leadership.
- Ability to simplify complex technical topics for senior audiences.
- Academic qualification (preferably Master’s or PhD) in Statistics, Data Science, physical or biological sciences, or related fields.
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