Data Scientist

Clariant Corporation•Palo Alto, CA

58d•$90,000 - $120,000

About The Position

Clariant is currently looking for a Data Scientist to support our project teams across R&D, manufacturing, and business development. The Data Scientist will work closely with cross-functional teams to design and maintain scalable data pipelines, develop machine learning models, and generate actionable insights that accelerate innovation. Candidates should have a strong foundation in data science and programming, with experience in Python, SQL, and related tools. This position is ideal for someone who is analytical, hands-on with data, and motivated to tackle complex problems while collaborating with diverse stakeholders. Clariant offers a competitive salary, annual bonus, PTO, and more. If you are ready to advance data-driven innovation in a dynamic workplace, apply today - we look forward to hearing from you! The salary range for this position in California is $90,000 - $120,000. This includes base salary and annual incentive bonus; final offer is based on skills, experience, and internal equity.

Requirements

Bachelor’s degree in Data Science, Computer Science, Engineering, or a related quantitative field
0–5 years of applied data science experience with programming skills in Python, C/C++ or C#, SQL
Strong problem-solving, communication, and collaboration skills, with the ability to manage multiple projects in a dynamic R&D environment

Nice To Haves

Experience with high-throughput experimentation, catalysis research, or materials informatics is highly desirable
Familiarity with ELNs, LIMS, or industrial data systems is a plus

Responsibilities

Design, build, and maintain scalable data pipelines to process and analyze high-throughput experimental and process data efficiently, ensuring reproducibility, reliability, and actionable insights
Develop and maintain robust code using Python, C/C++, SQL, BitBucket, and other tools, while ensuring solutions are reproducible and maintainable in a fast-paced research environment
Preprocess, clean, and transform raw experimental data into structured formats suitable for modeling, overcoming challenges of high-volume, heterogeneous datasets
Analyze complex datasets for trends, patterns, and correlations, presenting clear, research- and business-focused insights to stakeholders across R&D, manufacturing, business development, and IT
Advance department expertise in data science and machine learning, staying current with emerging technologies and techniques to maintain a competitive edge in high-throughput experimentation and materials informatics
Collaborate with cross-functional teams to understand data requirements and deliver solutions that meet business and research goals, balancing diverse stakeholder expectations and technical constraints
Upgrade and maintain automation and data retrieval systems to manage increasing data volumes, ensuring high-quality, reproducible results while adapting to evolving analytical platforms
Communicate findings effectively and contribute to team-oriented research, ensuring that solutions are both scientifically rigorous and practically applicable, while demonstrating strong problem-solving abilities and attention to detail