Senior Data Scientist - Forecasting

**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.