**About the Role**
We are hiring a Senior/Expert Data Scientist to build machine learning systems that power prediction, optimization, ranking, forecasting, and decision-making at scale.
You will work with large-scale behavioral, transactional, and location datasets to develop production-grade models that improve user experience, operational efficiency, and business outcomes. You will partner closely with Product Managers, Engineers, Data Scientists, and platform teams to deliver measurable impact through applied AI.
**Key Responsibilities**
- Own end-to-end ML projects from problem definition, data exploration, feature engineering, model development, deployment, and monitoring.
- Develop predictive models for forecasting, ranking, recommendation, optimization, and real-time decision making.
- Design and implement scalable deep learning and machine learning solutions using modern modeling techniques.
- Build production-ready AI systems with a strong focus on reliability, automation, model quality, and business impact.
- Design and execute experiments, A/B tests, and causal analyses to evaluate product and model improvements.
- Collaborate with cross-functional teams to translate business challenges into data-driven solutions.
- Research and evaluate emerging ML and AI techniques and drive their adoption into production systems.
- Communicate findings and recommendations to both technical and non-technical stakeholders.
**Required Qualifications**
- 7+ years of experience in Data Science, Machine Learning, Applied AI, or related fields.
- Strong programming skills in Python and SQL.
- Hands-on experience developing and deploying ML models in production environments.
- Strong understanding of machine learning fundamentals, statistics, probability, and experimental design.
- Experience with Deep Learning architectures such as Transformers, sequence models, recommendation models, ranking models, or forecasting models.
- Proficiency with PyTorch, TensorFlow, or equivalent ML frameworks.
- Experience working with large-scale datasets and distributed data platforms.
- Experience with model serving, monitoring, MLOps, and production ML lifecycle management.
- Strong problem-solving skills and the ability to translate ambiguous business problems into practical ML solutions.
**Preferred Qualifications**
Experience in one or more of the following areas:
- Forecasting and time-series modeling
- Recommendation systems
- Search and ranking
- Marketplace optimization
- Optimization and decision systems
- Spatio-temporal or location-based analytics
- Graph-based machine learning
- Reinforcement learning
Experience building real-time inference systems and streaming data pipelines.
Experience with large-scale experimentation and causal inference.
Familiarity with representation learning, embeddings, self-supervised learning, or foundation models.
Experience with cloud ML platforms and modern data infrastructure.
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Mid-Senior level
Full-time
IT Services and IT Consulting
