Dywidag is a global leader in construction and civil engineering specializing in innovative solutions.
Develop predictive models for pricing and sales forecasting, deliver MVPs.
9 days ago ago
Intermediate (4-7 years), Junior (1-3 years)
Full Time
Delhi, Delhi, India
Office Full-Time
Company Size
8,000 Employees
Service Specialisms
Monitoring
Maintenance
Inspection & Testing
Strengthening
Installation
Technical Support
Sector Specialisms
Energy
Transport
Marine
Bridges
Tunnels
Commercial Buildings
Residential Buildings
Industrial Buildings
Role
Description
data prep
mvp development
predictive modeling
machine learning
power bi
data quality
Collect, clean, and preprocess structured and unstructured data from diverse sources.
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.
Continuously improve data quality, analytical processes, and model performance.
Support various departments (e.g., Sales, Finance, Operations) with tailored predictive models and insights.
Stay current with the latest trends and technologies in data science, machine learning, and AI.
Develop, implement, and optimize statistical models, machine learning algorithms, and data mining techniques.
Clearly communicate findings and recommendations to stakeholders through presentations and documentation.
Visualize data insights using dashboards and reports, primarily with Power BI.
Requirements
azure
spark
python
power bi
data science
problem solving
Experience with big data technologies (e.g., Azure Data Factory, Synapse, Spark, Hadoop).
Demonstrated expertise in developing predictive models for pricing engines and sales forecasting.
2–3 years of proven experience as a data scientist in a business setting, supporting multiple departments/functions.
Proficiency in programming languages such as Python, R, or SQL.
Industry experience in Construction is preferred; experience in Manufacturing or Engineering-related Big Data is also relevant.
Excellent communication and collaboration abilities.
Experience with data visualization tools, especially Power BI.
Familiarity with Microsoft Azure cloud platforms is preferred.
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
Knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch).
Strong problem-solving skills and attention to detail.
Benefits
Information not given or found
Training + Development
Information not given or found
Interview process
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Visa Sponsorship
Information not given or found
Security clearance
Information not given or found
Company
Overview
1865
Years in Operation
The company has been providing construction and engineering solutions since 1865.
The company specializes in advanced construction technologies, offering innovative systems and services.
Dywidag has built a strong reputation for providing high-quality, long-lasting structures in a wide range of sectors.
Notable projects include complex infrastructure such as bridges, tunnels, and industrial plants.
The company’s engineering expertise spans from heavy civil works to specialized infrastructure solutions.
Dywidag focuses on delivering bespoke solutions tailored to clients' unique challenges, blending innovation with sustainability.
With a commitment to precision and reliability, Dywidag ensures every project meets the highest standards.
Its diverse portfolio covers energy, transport, water resources, and utility sectors, among others.
The company’s solutions are often highlighted by their ability to integrate cutting-edge technology with robust engineering practices.
Culture + Values
Five Continents
Global Presence
The company maintains a widespread presence across five continents, enabling it to connect communities and drive meaningful change on a global scale.
Prioritizing the well-being of employees and customers while driving sustainable growth through environmental protection, social responsibility, and long-term thinking.
Building strong, trust-based relationships through honesty, ethics, and consistency—core values that guide operations across every region.
Believing in the power of teamwork, shared goals, and open communication to pioneer innovative solutions for infrastructure challenges.
Environment + Sustainability
Net-zero target: pursue net-zero emissions (as part of ESG framework; no specific target year disclosed).
Environmental Protection pillar: increase infrastructure durability, reduce waste and resource usage, leverage circular business models, manage environmental hazards with goal of zero contamination.
Lifecycle approach: design high-quality, smart products to extend asset lifespan and minimize footprint.
Waste reduction: implement circular business models & responsible handling of hazardous materials.
Climate action: focus on environmental hazard management & zero incidents.
ESG disclosed in 2021 company presentation as formal framework (Environment, Social, Governance).
Inclusion & Diversity
provide equal employment opportunities via fair and transparent recruitment and market‑based salary policies.
promote openness & culture of trust, open‑door policy, anonymity, no retaliation for input.
zero tolerance for discrimination based on gender, sex, disability, age, religion, ethnic background, etc.
states its strength lies in ‘diversity of our people’ as part of global team.
no publicly disclosed gender ratios or specific numeric outcomes available.