Data Scientist (Time Series)

Fully remote | Complete engagement job

Founded in Palo Alto by Dr. Andrew Ng and Israel Niezen, Factored helps U.S. companies build and scale world-class AI, ML, and Data teams, powered by the top 1% of LATAM talent, with a defining purpose: To empower brilliant humans, unleash their potential, and amplify their impact in the world.

At Factored, you’ll be part of a community that values learning, ownership, and authenticity, where your growth is personal and your ideas matter. We’re transparent, curious, and collaborative. We strive for excellence, celebrate diversity, encourage curiosity, and build an environment where you can truly thrive.

We are currently looking for an exceptionally talented Senior Data Scientist - Time Series Specialist to join our team and help build cutting-edge solutions at the intersection of manufacturing and advanced analytics. In this role, you will design and deploy scalable ML systems that detect anomalies, uncover root causes, and transform complex manufacturing and test log data into actionable insights that drive product quality and operational efficiency.

Functional Responsibilities:

• Design and implement ML and statistical models for anomaly detection on large-scale manufacturing test logs and machine outputs.
• Work with high-volume time series and structured machine log data, meeting low-latency requirements in production environments.
• Build both real-time (live line) detection pipelines and post-hoc failure analysis and root cause analysis workflows.
• Translate domain expertise into scalable, production-ready systems, ensuring reliability, observability, and performance.
• Continuously evaluate and apply emerging techniques in machine learning and time series analysis to improve model performance and robustness.

Qualifications:

• 4+ years of experience in Data Science, Machine Learning, or a related field.
• Hands-on experience building anomaly detection models, ideally within manufacturing or industrial environments.
• Strong experience working with high-frequency time series data, including feature engineering for sequential signals.
• Proficiency in Python and SQL, with experience using ML libraries such as TensorFlow, PyTorch, or scikit-learn.
• Solid understanding of machine learning, statistical modeling, and data analysis techniques.
• Proven ability to work with large-scale datasets under low-latency constraints in production or near-production environments.
• Experience translating models into production systems (e.g., basic ML deployment, experiment tracking, or CI/CD workflows) is a plus.
• Strong communication skills in English (B2–C2), with the ability to clearly explain complex technical concepts and collaborate across teams.

 

Our Benefits:

• Ownership through equity participation.
• Annual company retreat.
• Education bonus for continuous learning.
• Company-wide winter break.
• Paid time off.
• Optional in-person events and meetups.
• Tailored career roadmaps.
• High-performance culture.

 

At Factored, we believe that passionate, smart people expect honesty and transparency, as well as the freedom to do the best work of their lives while learning and growing as much as possible. Great people enjoy working with other passionate, smart people, so we believe in hiring right, and are very selective about who joins our team. Once we hire you, we will invest in you and support your career and professional growth in many meaningful ways. We hire people who are supremely intelligent and talented, but we recognize that intelligence is not enough. Perhaps more importantly, we look for those who are also passionate about our mission and are honest, diligent, collaborative, kind to others, and fun to be around. Life is too short to work with people who don’t inspire you.     We are a transparent workplace, where EVERYBODY has a voice in building OUR company, and where learning and growth are available to everyone based on their merits, not just on stamps on their resume. As impressive as some of the stamps on our resumes are, we recognize that human talent and passion exist everywhere, and come from many backgrounds, so stamps matter much less than results. All of us are dedicated doers and are highly energetic, focusing vehemently on execution because we know that the best learning happens by doing. We recognize that we are creating OUR COMPANY TOGETHER, which is not only a high-performing fast-growing business but is changing the way the world perceives the quality of technical talent in Latin America. We are fueled by the great positive impact we are making in the places where we do business and are committed to accelerating careers and investing in hundreds (and hopefully thousands) of highly talented data science engineers and data analysts.    In short, our business is about people, so we hire the best people and invest as much as possible in making them fall in love with their work, their learning, and their mission.  When not nerding out on data science, we love to make music together, play sports, play games, dance salsa, cook delicious food, brew the best coffee, throw the best parties, and generally have a great time with each other.