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Data Science - Job Opportunity at Metropolis

Bengaluru, India
Full-time
Mid-level
Posted: July 21, 2025
On-site
INR 12-18 lakhs per annum (USD 14,500-21,500). This estimate reflects the mid-level experience requirement, Bangalore's competitive tech market, and the specialized nature of computer vision and AI applications. Metropolis as a well-funded AI startup likely offers equity compensation and performance bonuses that could significantly increase total compensation.

Benefits

Opportunity to work with cutting-edge AI and computer vision technology in a rapidly growing market segment
Exposure to world-class product leaders and engineers providing exceptional mentoring and learning opportunities
Inclusive culture that values diverse perspectives and merit-based decision making
Direct involvement in building revolutionary checkout-free experiences that impact millions of consumers
Career growth in the intersection of parking, mobility, and real estate technologies

Key Responsibilities

Drive strategic business decisions by extracting actionable insights from large-scale datasets across multiple business units
Architect and deploy production-grade machine learning models that directly solve critical business challenges and revenue optimization
Lead experimental design through A/B testing frameworks and advanced statistical analyses to validate product hypotheses
Partner with executive leadership across product, engineering, and marketing to define data strategy and analytics roadmaps
Translate complex analytical findings into executive-level presentations that influence company-wide strategic initiatives
Build comprehensive business intelligence infrastructure including real-time dashboards and KPI monitoring systems
Maintain competitive advantage by researching and implementing cutting-edge data science methodologies and AI technologies

Requirements

Education

Bachelor's/Master's degree in Computer Science, Mathematics, Statistics, or related field

Experience

3+ years

Required Skills

Strong knowledge of Python/R and SQL Hands-on experience with machine learning frameworks (e.g., scikit learn, tensroflow, pytorch) Experience with big data tools (e.g., Spark, Hadoop) is a plus Familiarity with data visualization tools Strong analytical, problem-solving, and communication skills Experience with cloud platforms preferably AWS (S3, Sagemaker, Airflow etc) Strong SQL skills, with experience in Snowflake, MySQL, and PostgreSQL Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker)
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Sauge AI Market Intelligence

Industry Trends

The computer vision and AI-powered retail technology sector is experiencing explosive growth, with checkout-free technology expanding beyond Amazon Go to parking, retail, and mobility sectors. Companies leveraging computer vision for real-world applications are attracting significant venture capital investment and scaling rapidly across global markets. Smart parking solutions are becoming critical infrastructure investments for smart cities initiatives worldwide, with IoT and AI-driven parking management systems projected to reach $11.6 billion by 2025. The convergence of mobility-as-a-service and autonomous vehicle preparation is driving demand for frictionless parking experiences. Data science roles in computer vision and real-world AI applications are commanding premium salaries due to the specialized nature of working with visual data, real-time processing requirements, and the business-critical nature of customer experience optimization in physical spaces.

Role Significance

Likely part of a 8-15 person data and engineering organization within a growing startup environment. The role suggests working within a collaborative data team while interfacing regularly with product managers, engineers, and business stakeholders across the organization.
This is a mid-level individual contributor role with significant strategic impact. The position involves direct collaboration with cross-functional leadership and requires independent project ownership, suggesting the role carries substantial influence on product direction and business outcomes despite not being explicitly managerial.

Key Projects

Development and optimization of computer vision algorithms for real-time vehicle recognition and tracking systems Building predictive models for parking demand forecasting and dynamic pricing optimization Creating customer behavior analytics platforms to optimize user experience and reduce friction in parking transactions Implementing A/B testing frameworks for mobile app features and physical infrastructure changes Developing business intelligence dashboards for operational metrics, revenue tracking, and customer engagement analysis

Success Factors

Ability to translate complex computer vision and machine learning concepts into business value propositions that resonate with non-technical stakeholders and drive strategic decision-making Strong foundation in both theoretical data science principles and practical implementation skills, particularly the ability to deploy models in production environments that handle real-time traffic and customer transactions Cross-functional collaboration excellence, as success requires working closely with hardware engineers, mobile developers, business development teams, and operations staff to create integrated solutions Adaptability and learning agility to keep pace with rapidly evolving AI technologies and business requirements in the emerging checkout-free technology sector

Market Demand

Very High - Computer vision data scientists are in extremely high demand as more companies digitize physical experiences. The combination of AI expertise and real-world application experience makes this a particularly valuable skill set in the current market.

Important Skills

Critical Skills

Python/R and SQL proficiency is essential as these form the foundation for all data manipulation, analysis, and model development work. The ability to work efficiently with large datasets and complex queries directly impacts productivity and project success in this role. Machine learning frameworks expertise (scikit-learn, TensorFlow, PyTorch) is crucial because the role involves building and deploying production models for computer vision applications. Real-time processing requirements and model performance optimization are critical for customer experience. Statistical analysis and A/B testing capabilities are vital for validating product hypotheses and measuring the impact of changes to both digital interfaces and physical infrastructure. The ability to design rigorous experiments is essential for data-driven decision making.

Beneficial Skills

Cloud platform expertise, particularly AWS, becomes increasingly valuable as the company scales infrastructure and requires more sophisticated MLOps capabilities for model deployment and monitoring Big data tools experience (Spark, Hadoop) will be important as transaction volumes grow and the company expands to new markets, requiring processing of massive datasets efficiently Data visualization skills using tools like Tableau or Looker are valuable for creating executive dashboards and communicating insights effectively to stakeholders across the organization

Unique Aspects

Opportunity to work on computer vision applications that impact millions of daily consumer interactions, providing immediate real-world validation of data science work rather than abstract modeling exercises
Intersection of multiple high-growth technology sectors including AI, IoT, smart cities, and mobility-as-a-service, offering exposure to diverse technical challenges and market opportunities
Direct involvement in building the foundation for checkout-free experiences beyond parking, positioning for potential expansion into retail, hospitality, and other physical experience sectors
Combination of hardware integration challenges with software data science, requiring understanding of both digital analytics and physical world constraints

Career Growth

Progression to senior individual contributor roles typically occurs within 2-3 years with strong performance. Management opportunities may emerge within 3-5 years as the company scales and requires dedicated data science leadership.

Potential Next Roles

Senior Data Scientist with team leadership responsibilities and ownership of major product initiatives Data Science Manager leading a team of data scientists and analysts across multiple product verticals Principal Data Scientist focusing on advanced research and development of next-generation computer vision applications Product Manager for data-driven features, leveraging deep technical expertise to guide product strategy

Company Overview

Metropolis

Metropolis represents a well-funded AI startup that has successfully commercialized computer vision technology for real-world applications, moving beyond proof-of-concept to serving millions of consumers. The company appears to be in a growth phase, expanding beyond parking into broader checkout-free experiences, indicating strong product-market fit and investor confidence.

As a pioneer in AI-powered parking solutions, Metropolis holds a competitive advantage in the smart mobility sector. The company's focus on frictionless experiences positions them well for the broader trend toward seamless digital-physical integration, potentially competing with tech giants while maintaining specialized domain expertise.
The Bangalore location suggests Metropolis is establishing a significant engineering presence in India's premier technology hub, likely seeking to leverage local AI and machine learning talent while maintaining cost efficiency. This indicates serious commitment to scaling their technical capabilities in the region.
The emphasis on inclusive culture, merit-based decisions, and world-class talent suggests a performance-driven environment that values innovation and diverse perspectives. As a growing startup, the culture likely emphasizes rapid learning, ownership, and direct impact on business outcomes.
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