Data Scientist - Forecasting

Company Description

BLEND360 is adding to our team of passionate people who are revolutionizing the world of Data Science. We are an award-winning, new breed Data ScienceData EngineeringBI Solutions Company focused on powering exceptional results to our Fortune 500 clients. We are a growing company – born at the intersection of advanced analytics, data and technology. 

Our new Director of Data Engineering will be in the forefront of driving major projects within BLEND360 and working with our data engineering team to develop innovative data driven solutions that integrate distributed sources of data, perform large scale learning and reasoning, and integrate results.

Job Description

We are looking for an experienced Data Scientist with a specialization in forecasting to join our data science team. The ideal candidate will have a deep understanding of statistical and machine learning techniques for time series forecasting and demand prediction. In this role, you will drive business value by developing accurate forecasting models and delivering actionable insights to optimize decision-making processes across the organization.

Key Responsibilities:

• Develop and implement advanced time series forecasting models to predict key business metrics (e.g., sales, demand, inventory, etc.).
• Analyze historical data to identify trends, seasonality, and other patterns that can be leveraged for accurate forecasting.
• Collaborate closely with client’s cross-functional teams such as Supply Chain, Finance, and Marketing to understand business needs and deliver tailored forecasting solutions.
• Build and optimize machine learning models for forecasting using state-of-the-art techniques (e.g., ARIMA, Prophet, LSTM, etc.).
• Design and run experiments to validate forecasting models and continuously improve their accuracy and reliability.
• Communicate complex data-driven insights and forecasting results to both technical and non-technical stakeholders.
• Ensure high-quality data inputs for forecasting models by working with data engineering teams to improve data collection, transformation, and integration processes.
• Stay current with the latest advancements in forecasting methodologies, tools, and techniques, and apply them to enhance existing models.
• Provide thought leadership in forecasting and predictive analytics, driving innovation within the data science team.
• Mentor junior team members and help establish best practices for forecasting across the organization.

Qualifications

• Master’s or Ph.D. in Data Science, Statistics, Economics, Applied Mathematics, or a related quantitative field.
• 4+ years of experience in developing and deploying forecasting models in a business environment.
• Expertise in time series analysis and forecasting techniques, including ARIMA, SARIMA, Holt-Winters, and advanced machine learning methods like gradient boosting, neural networks (e.g., LSTM, GRU), etc.
• Proficiency in programming languages such as Python or R, with strong experience in data manipulation, model building, and statistical analysis.
• Hands-on experience with forecasting tools and libraries, such as Prophet, scikit-learn, TensorFlow, PyTorch, etc.
• Strong understanding of data structures, data wrangling, and working with large datasets.
• Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and working in a distributed data environment is a plus.
• Excellent problem-solving skills and ability to translate complex data into actionable insights.
• Strong communication and presentation skills, with the ability to convey complex concepts to both technical and non-technical audiences.
• Experience with visualization tools like Tableau, Power BI, or similar to present forecasting outcomes.
• Ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications:

• Experience with demand forecasting, sales forecasting, or supply chain optimization in industries such as retail, manufacturing, or finance.
• Familiarity with statistical testing and experimentation (e.g., A/B testing).
• Experience deploying models in production environments and collaborating with engineering teams to build scalable solutions.
• Previous experience in a consulting or client-facing role is a plus.