Data Scientist
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Job Description
Lead Data Engineer at Cushman & Wakefield architecting data platforms and leading advanced analytics solutions. Collaborating across teams to enhance data availability, quality, and insights.
Responsibilities:
- Partner with business leadership to identify impactful areas for the application of AI and ML.
- Lead Data science and Data driven Analytics engagements across clients covering various sectors.
- Design and optimize ML models for predictive analytics and prescriptive analytics enabled solutions
- Explore cutting-edge techniques in AI and ML to enhance model performance.
- Maintain generative AI models along with development and updating of code and process documentation
- Partner with data stewards to improve data availability and quality while ensuring compliance
- Partner with technology teams to deploy AI and ML solutions in scalable environments.
- Use business intelligence tools for better visualization and transparency of data driven insights
- Managing a team of data engineers, data scientists, and analytics professionals to deliver data-driven insights and solutions to support business decision-making.
- Track latest AI innovations and build relevant PoCs to further our capabilities
- Participate in organization building, hiring, partnerships, conferences etc.
Requirements:
- Experience in Databricks
- Advanced statistics & machine learning (e.g., causal inference, experimentation, forecasting, NLP, recommender systems, or deep learning—depending on the company)
- Strong programming skills Python or R (production-quality code)
- SQL mastery (complex queries, performance tuning)
- Experience deploying models to production
- Model lifecycle, monitoring, retraining, data drift
- Solid data engineering awareness
- Data pipelines, feature stores, cloud platforms (Azure/ML flow)
- Hands-on experience with machine learning pipelines or integrating data engineering with advanced analytics and AI workflows.
- Familiarity with data governance frameworks, including data lineage, cataloging, and compliance (e.g., GDPR, HIPAA).
- Background in delivering data-driven solutions for commercial real estate applications
- Degree in IT, Engineering, computer sciences, business IT degree or in any quantitative discipline
Benefits:
- health insurance
- vision insurance
- dental insurance
- flexible spending accounts
- health savings accounts
- retirement savings plans
- life insurance programs
- disability insurance programs
- paid time off
- unpaid time away from work
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