Data Scientist
5 months ago
**Key Responsibilities**:
**Data Analysis & Modeling**: Develop and implement advanced algorithms and models to analyze large datasets, identifying trends, patterns, and anomalies in the real estate market.
**Predictive Analytics**: Design predictive models for real estate pricing, demand forecasting, and risk assessment.
**Market Research**: Stay abreast of market conditions and shifts,integrating this knowledge into data-driven reports and recommendations.
**Collaboration**: Work closely with the investment, marketing, and sales teams to provide data-driven insights and strategies.
**Data Collection & Cleaning**: Identify and acquire new data sources, ensuring they are clean, accurate, and reliable.
**Visualization**: Create interactive dashboards and visual reports to present findings in a clear and concise manner to stakeholders.
**Continuous Learning**: Remain updated with the latest technologies, techniques, and best practices in data science and real estate analytics.
**Qualifications**:
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
- Proven experience as a data scientist, preferably with exposure to the real estate sector.
- Strong proficiency in programming languages such as Python, R, and SQL.
- Experience with data visualization tools like Tableau, Power BI, or equivalent.
- Familiarity with real estate databases, GIS tools, and geospatial data analysis.
- Excellent analytical and problem-solving skills.
- Strong communication skills to effectively collaborate with cross-functional teams.
**Personal Attributes**:
- Detail-oriented with a passion for precision.
- Curiosity and eagerness to continuously learn and adapt.
- Ability to translate complex data findings into actionable business insights.
**Job Types**: Full-time, Permanent
Pay: From ₹40,000.00 per month
**Benefits**:
- Health insurance
- Paid time off
Schedule:
- Day shift
- Morning shift
Supplemental pay types:
- Performance bonus
**Experience**:
- total work: 3 years (preferred)
Work Location: In person
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