Data Scientist
3 days ago
Data Scientist - Deep Learning Based Demand Forecasting
Fetcherr experts in deep learning, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.
We are seeking a talented and self-driven experienced Data Scientist to help advance our machine learning capabilities.This is a key role for someone passionate about leveraging machine learning to solve complex, real-world problems and deliver measurable business impact.
Responsibilities:
- Develop and implement state-of-the-art econometric and machine learning models for demand forecasting.
- Conduct research and experimentation to evaluate novel approaches for improving accuracy, robustness, and scalability.
- Collaborate with cross-functional teams (including product, data engineering, and backend) to deploy ML systems in production.
- Mentor junior team members and promote best practices across modeling, experimentation, and code quality.
- Clearly communicate complex technical findings to non-technical stakeholders, including product leaders and executives.
You'll be a great fit if you have:
- 5+ years of hands-on experience in data science and machine learning with a proven record of leveraging modeling into business outcomes.
- Proficiency in Python and its ML/data stack (e.g., PyTorch or TensorFlow, Pandas, NumPy, Scikit-learn, SQL).
- Expertise in time-series forecasting, ideally Deep Learning based, preferably in demand prediction or related areas.
- Domain expertise in revenue management related pipelines, domains, problems.
- Feature engineering, feature importance testing, per sample explainability based experience.
- Master's or PhD in Computer Science, Machine Learning, Statistics, Engineering or a relevant field.
- Publications in top-tier, peer-reviewed ML/AI venues (e.g. ICLR, ICML, NIPS, etc.)
- Solid understanding of ML production workflows (versioning, testing, reproducibility, and deployment).
- Excellent communication and collaboration skills.
Nice to have:
- Experience applying ML in domains like finance, trading, reinforcement learning, or NLP.
- Familiarity with cloud based solutions on GCP platform (e.g., Vertex AI, PubSub, Cloud Run Functions).
- Strong data visualization and exploratory data analysis skills.
- Familiarity with code optimization, containerization (e.g., Docker), CI/CD, or cloud-native architectures.
- Participation in competitive programming or data science challenges (e.g., Kaggle).
If you're excited about building impactful AI systems in a high-growth startup environment, and want to help redefine how industries price, forecast, and optimize, we'd love to hear from you.
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