Purpose of the Job

We are seeking a highly skilled and motivated Data Scientist to join our team. The ideal candidate will have 2–3 years of hands-on experience as a data scientist in a business environment, supporting multiple departments and functions with predictive analytics and rapid development of minimal viable products (MVPs). A strong emphasis is placed on experience with pricing engines and sales forecasting solutions. You will be responsible for analyzing large datasets, building predictive models, and enabling data-driven decision-making across the organization.

Key Responsibilities

Collect, clean, and preprocess structured and unstructured data from diverse sources.
Develop, implement, and optimize statistical models, machine learning algorithms, and data mining techniques.
Rapidly prototype and deliver MVPs to address business needs, especially in pricing and sales forecasting.
Collaborate with the Global BI Team and cross-functional stakeholders to understand requirements and translate them into actionable analytical solutions.
Support various departments (e.g., Sales, Finance, Operations) with tailored predictive models and insights.
Visualize data insights using dashboards and reports, primarily with Power BI.
Clearly communicate findings and recommendations to stakeholders through presentations and documentation.
Continuously improve data quality, analytical processes, and model performance.
Stay current with the latest trends and technologies in data science, machine learning, and AI.

Required Qualifications

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
2–3 years of proven experience as a data scientist in a business setting, supporting multiple departments/functions.
Demonstrated expertise in developing predictive models for pricing engines and sales forecasting.
Proficiency in programming languages such as Python, R, or SQL.
Experience with data visualization tools, especially Power BI.
Familiarity with Microsoft Azure cloud platforms is preferred.
Strong problem-solving skills and attention to detail.
Excellent communication and collaboration abilities.

Preferred Qualifications

Experience with big data technologies (e.g., Azure Data Factory, Synapse, Spark, Hadoop).
Knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch).
Industry experience in Construction is preferred; experience in Manufacturing or Engineering-related Big Data is also relevant.

DYWIDAG

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