Senior Data Scientist - Demand Forecasting

We are seeking a highly skilled and experienced Senior Data Scientist with expertise in forecasting to join our Tredence team. In this role, you will lead the development of predictive models, implement advanced statistical and machine learning techniques, and provide actionable insights to drive strategic decision-making. Your work will directly impact our ability to anticipate trends, optimize operations, and achieve our business objectives.

Key Responsibilities:

• Develop, validate, and implement advanced forecasting models using statistical and machine learning techniques to predict key business metrics.
• Conduct exploratory data analysis (EDA) to identify trends, patterns, and insights that inform forecasting strategies.
• Collaborate with cross-functional teams to understand business objectives and ensure alignment between data-driven insights and organizational goals.
• Enhance and optimize existing forecasting models by incorporating external data sources and novel approaches.
• Communicate complex analytical results to non-technical stakeholders through clear and concise presentations, visualizations, and reports.
• Lead the implementation of best practices in model development, version control, and performance monitoring.
• Mentor junior data scientists and contribute to a culture of continuous learning and innovation within the data science team.
• Stay updated with the latest advancements in forecasting methodologies and technologies.

Qualifications:

Required:

• Engineering/Masters or Ph.D. in Data Science, Statistics, Applied Mathematics, Computer Science, or a related field.
• 5+ years of hands-on experience in data science, with a strong focus on forecasting.
• Proficiency in programming languages such as Python or SQL and experience with libraries like Prophet, ARIMA, or TensorFlow for time-series forecasting.
• Strong knowledge of statistical methods, time-series analysis, and machine learning algorithms relevant to forecasting.
• Experience with cloud platforms such as AWS, GCP, or Azure, and tools like Databricks for model deployment.
• Expertise in SQL for data extraction and transformation.
• Proven ability to handle large datasets and work with distributed systems like Hadoop or Spark.
• Exceptional problem-solving skills and attention to detail.
• Excellent communication and interpersonal skills for cross-functional collaboration.