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Tephra
Position Details: Director - Data & Decision Intelligence Scientist

Location San Francisco, California

Intern
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EMCOR
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Hankey Group
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Tephra
Tephra

Position Details: Director - Data & Decision Intelligence Scientist

location San Francisco, California

Job Type Intern

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Description:

Role: Director - Data & Decision Intelligence Scientist
Location: San Francisco, CA (Bay Area)


Role Overview

In an age drowning in data but starving for insight, we’re seeking rare minds who can transmute raw data into business gold.

We’re looking for exceptional analytical minds from premier institutions to join our Decision Intelligence team. In this role, you’ll leverage descriptive, inquisitive, predictive and prescriptive analytics to transform complex data into clear, actionable insights that shape our business strategy and product development. You’ll work across business domains to solve challenging problems and drive data-informed evidence-based decision-making throughout.

If you’re ready to move beyond conventional data science and develop the intelligence that shapes the future of our business, we’re eager to meet you.

Why Join Us

We are not just a lab; we are solving problems that people don’t even know exist, now or in the future. We make AI real. We are the weavers of the new digital and intelligent fabric to make the world work better. Code doesn’t solve problems, threading that into existences by people of intent is what does. We do this for 90% of Fortune 500 of our partners and many more. Together we mine the unlimited potential and add at back to the world.

You’ll be at the bleeding edge of AI, Data science and analytics technology, redefining how that applies to business and society at large. You’ll gain exposure to diverse problem domains while building your expertise. Top performers have pathways to become Research Scientists, Technical Leads, or AI Architects, with opportunities to present at leading conferences and contribute to patents. You will also have the opportunity to interact with CXOs of top companies and peek inside their minds.

Join us to build the future of intelligent enterprises while working alongside industry leaders in a collaborative, innovation-driven environment, that values your fresh perspectives and technical excellence.

Key Responsibilities
Drive Decisions

- Apply sophisticated math-stat methods, algorithms, modern learning techniques and optimization models to drive decisions
- Develop descriptive, causal, predictive and decision models for various problems
- Communicate complex findings in accessible ways to help stakeholders make informed decisions
- Transform and boost data from various sources to ensure high-quality inputs for model development and analysis
- Design and implement end-to-end analytical frameworks

Do Science

- Create reproducible research methodologies that can be applied across multiple domains with product teams, engineering and executives to identify high-value opportunities
- Collaborate with improvements and make model value real
- Develop metrics, KPIs, reports and dashboards that accurately measure business performance and impact

Collaborate and Conquer

- Translate analytical insights into strategic recommendations with clear implementation paths
- Bring science into Data science with collaboration and building reusable component paths that empower non-technical teams to leverage data insights
- Design experiments that settle strategic debates with evidence instead of opinions

Qualifications:
 - MS or PhD in Statistics, Mathematics, Computer Science, or related quantitative field from aop university
 - Strong foundation in statistical analysis, hypothesis testing, and experimental design
 - Deep concepts in algorithms and optimization
 - Proficiency in Python / R / SQL / C++ for data analysis and modelling
 - Exposure to data visualization tools (Tableau, Power BI) or libraries (Matplotlib, Seaborn etc.)
 - Excellent problem-solving skills and ability to translate business questions into analytical frameworks

Preferred
 - Experience with A/B testing and causal inference methods
 - Familiarity with big data technologies (Spark, Hadoop)
 - Knowledge of deep learning frameworks and applications
 - Development of Optimization models in Gurobi, CPLEX or equivalent
 - Prior internships or projects involving real-world analysis and modelling



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