Data Scientist

Job Description

Summary:
We’re looking for a hands-on Data Scientist who thrives in solving ambiguous problems with messy data and delivering impactful, production-ready machine learning solutions. You’ll work closely with cross-functional teams to turn complex business questions into clear, data-driven actions that move the needle. If you combine technical mastery with a strong sense of product intuition and love experimenting to find what really works, this role is for you.

What You’ll Own:

• Design and implement advanced predictive models that directly influence product features and user engagement strategies.
• Translate ambiguous business questions into clear, testable hypotheses and actionable insights through creative data exploration.
• Build end-to-end data science solutions: from data ingestion and cleaning pipelines to deploying models in production environments.
• Collaborate closely with product managers, engineers, and designers to embed data-driven decision-making in every stage of product development.
• Develop custom metrics and monitoring systems to track model performance and business impact in near real-time.
• Lead efforts to improve data quality, champion best practices in experiment design, and push the boundaries of automated feature engineering.

What We Expect From You:

• Proven experience working with messy, incomplete datasets where cleaning and feature engineering were critical to success—not just textbook cases.
• Expertise in Python or R, with a strong command of libraries such as pandas, scikit-learn, TensorFlow/PyTorch, and SQL for data manipulation and modeling.
• Demonstrable skills in deploying machine learning models in production, including containerization (Docker, Kubernetes) and API development.
• A solid understanding of causal inference techniques and experience applying them to measure real impact beyond correlation.
• Fluency in statistical inference and experimental design, capable of guiding product teams on A/B testing nuances, power calculations, and bias mitigation.
• Experience with time-series forecasting, anomaly detection, or natural language processing is a strong plus.
• Ability to communicate complex technical concepts and model insights clearly and persuasively to non-technical stakeholders.
• Curiosity and intellectual humility—comfortable admitting when the data doesn’t support a hypothesis and iterating quickly.

Bonus Points For:

• Open source contributions in data science or machine learning.
• Experience working in highly regulated industries with strict data governance (e.g., healthcare, finance).
• Familiarity with cloud platforms (AWS, GCP, Azure) and their managed ML services.
• Background in engineering or product roles that enrich your ability to bridge data science and software development.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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