Description
Duties & Responsibilities & Modeling :
- Develop and deploy time-series forecasting models (e.g., Prophet, ARIMA, DeepAR, LSTM, Temporal Fusion Transformer) to predict demand, revenue, and promotion lift.
- Apply advanced statistical and causal-inference methods to understand promotion effects and seasonality.
- Build dynamic pricing and promotion recommendation models leveraging reinforcement learning or multi armed bandits.
AI System Design
- Architect ML pipelines for promotion targeting and ROI optimization
- Design end to end data workflows from data ingestion to model deployment integrated with
production APIs and dashboards.
- Contribute to scalable model monitoring, retraining, and drift detection.
Data Engineering & APIs
- Work with SQL databases, data warehouses (Azure SQL, Snowflake, Databricks Delta, etc.), and APIs to retrieve, transform, and operationalize data.
- Collaborate with cloud teams to ensure efficient and secure deployment of AI services (Azure
or GCP).
Requirements
Basic Qualifications :
- Masters degree in computer science, Data Science, Statistics, or a related field.
- 6+ years of experience in designing, developing, and deploying AI/ML solutions.
- Proficiency in Python and its AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Strong expertise in forecasting and time series analysis techniques.
- Solid understanding of machine learning algorithms and statistical modeling.
- Experience with data preprocessing, feature engineering, and model evaluation.
- Familiarity with version control systems (e.g., Git) and collaborative development workflows.
- Strong problem-solving and analytical skills.
Preferred Qualifications
- Ph.D. in Computer Science, Data Science, Statistics, or a related field.
- Experience with cloud platforms (e.g., Azure, GCP) for deploying AI solutions.
- Knowledge of advanced time series models (e.g., ARIMA, Prophet, LSTMs, Transformers).
- Expertise in handling large datasets and distributed computing frameworks (e.g., Spark, Dask).
- Familiarity with MLOps practices and tools for model deployment and monitoring.
- Strong understanding of statistical programming and data visualization tools (e.g., Matplotlib, Seaborn).
- Experience with database systems and query optimization.
- Excellent communication skills for cross-functional collaboration and presenting technical concepts.
(ref:hirist.tech)
