**Position Overview:**
We are looking for a highly skilled Data Scientist with extensive experience in forecasting, particularly in demand or sales forecasting. The ideal candidate will have a strong background in time series analysis, advanced machine learning models, and deep learning techniques. In addition, the candidate should have hands on experience of building ML solutions on AWS.
**Key Responsibilities:**
- Fast-paced experimentation, development and implementation of advanced forecasting models for demand or sales forecasting.
- Utilize time series analysis, statistical methods, and machine learning algorithms to build accurate and scalable forecasting solutions.
- Design and develop global forecasting models that consider economic, demographic, historical trends, and other relevant factors.
- Work closely with cross-functional teams to gather requirements, analyze data, and deliver actionable insights.
- Collaborate with data engineers to deploy and integrate forecasting solutions into production systems.
- Conduct thorough evaluation and validation of forecasting models to ensure accuracy and reliability.
- Stay updated on the latest advancements in forecasting techniques, machine learning algorithms, and cloud technologies.
**Qualifications:**
- Master's degree in Statistics, Data Science, Computer Science, or related field.
- Minimum of 3 years of experience in data science, with a focus on forecasting.
- Strong proficiency in time series analysis, statistical modeling, and machine learning algorithms.
- Advanced experience with AWS services such as SageMaker, S3, EC2, Lambda, etc.
- Demonstrated expertise in building and deploying ML solutions at scale, preferably in a cloud environment.
- Excellent problem-solving skills and ability to thrive in a fast-paced, collaborative environment.
- Strong communication and presentation skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders.
**Great to have:**
- Familiarity with deep learning techniques for time series forecasting (e.g., LSTM, GRU).
- Experience with big data technologies such as Spark.