Lead Data Scientist, Silicon Data, US

Position Overview

We are seeking an experienced Data Scientist / Quant Analyst who is passionate about leveraging data to develop mathematical models, generate insights, and tell compelling stories. The ideal candidate has a deep understanding of the tools and methodologies used in data science and quantitative analysis and can apply these to complex, real-world problems. This role requires a combination of strong analytical skills, creativity, and the ability to communicate complex concepts effectively.

Key Responsibilities

- Model Development: Design, implement, and validate advanced mathematical models to support decision-making, product development, and market analysis.

- Data Analysis: Perform exploratory data analysis, data cleaning, and data mining to extract meaningful insights from large, complex datasets.

- Insight Generation: Utilize statistical methods, machine learning algorithms, and quantitative techniques to uncover trends, patterns, and insights that drive business decisions.

- Storytelling: Translate complex data findings into clear, actionable narratives that can be understood by both technical and non-technical stakeholders.

- Tool Proficiency: Utilize standard data science tools such as Python, R, SQL, and various data visualization platforms (e.g., Tableau, Power BI) to conduct analysis and present findings.

- Collaboration: Work closely with cross-functional teams, including product managers, engineers, and business leaders, to ensure that data-driven insights are integrated into company strategies.

- Reporting: Develop and maintain dashboards, reports, and visualizations that track key metrics and provide ongoing insights into business performance.

- Research & Development: Stay updated on the latest trends in data science, quantitative analysis, and market developments to continuously improve our models and methodologies.

Qualifications

- Educational Background: Master’s or PhD in Data Science, Mathematics, Statistics, Economics, Computer Science, or a related field.

- Experience: 5+ years of experience in data science, quantitative analysis, or a related role, preferably within the tech, finance, or data industries.

- Technical Skills:

- Proficiency in programming languages such as Python, R, and SQL.

- Strong experience with data visualization tools like Tableau, Power BI, or similar.

- Expertise in statistical analysis, machine learning, and mathematical modeling.

- Experience with big data tools (e.g., Hadoop, Spark) is a plus.

- Analytical Thinking: Ability to think critically and solve complex problems using quantitative methods and data-driven insights.

- Communication Skills: Strong verbal and written communication skills, with the ability to explain complex technical concepts to diverse audiences.

- Business Acumen: Understanding of business strategy and the ability to align data insights with organizational goals.

- Attention to Detail: High level of accuracy and attention to detail in analysis and model development.