Associate Business Analyst (WFH)

About the job:About the Role

We're building a next-generation online property marketplace, connecting buyers, renters, sellers and agents through listings, search, valuations and market insights. You'll bridge business, product and engineering, defining what to measure and building the AI/ML models and data pipelines that power platform features and decisions.

Key Responsibilities

Analytics: Define and track marketplace KPIs (listing volume, engagement, enquiry conversion, agent retention, revenue per listing); build executive and self-serve dashboards; design and evaluate A/B tests.

Requirements: Gather needs from product, sales and marketing stakeholders and translate them into data specifications.

Data engineering: Design data models for listings, properties, suburbs, agents and users; build ETL/ELT pipelines for listing feeds, ABS/census, geospatial and third-party data; ensure quality and compliance with the Privacy Act.

AI/ML: Develop and deploy automated valuation models, recommendations, search ranking, suburb price forecasting, lead scoring and duplicate/fraud detection.

NLP, vision and GenAI: Extract features from listing text and photos; explore semantic search, conversational property search and listing description generation.

MLOps: Work with engineering to productionise models and monitor drift, bias and performance.

Communication: Present insights to non-technical audiences and mentor junior analysts.

Required Skills & Experience

1+ years in data analytics or data science, ideally in marketplace, proptech, e-commerce or classifieds

At least one ML model taken from idea to production

Advanced SQL; Python (pandas, scikit-learn, XGBoost/LightGBM) and/or R

ML fundamentals: regression, classification, clustering, time series, recommenders

BI tools (Tableau, Power BI or Looker) and product analytics (GA4, Amplitude or Mixpanel)

Cloud data stack: AWS/GCP/Azure, Snowflake/BigQuery, dbt, Airflow

Experimentation and statistical testing

Strong stakeholder management and data storytelling; understanding of marketplace dynamics

Desirable

Deep learning (PyTorch/TensorFlow), LLMs, RAG and vector databases

Geospatial analysis (PostGIS, GeoPandas, H3)

MLOps (MLflow, SageMaker/Vertex AI, Docker, CI/CD)

Knowledge of Australian property data (CoreLogic/Cotality, PropTrack, ABS, land registries)

Responsible AI and explainability (SHAP, LIME)Who can apply:Only those candidates can apply who:have minimum 1 years of experienceSalary:₹ 2,00,000 - 2,40,000 /yearExperience:1 year(s)Deadline:[hidden]:59:59Skills required:Data Analytics and Research and AnalyticsOther Requirements:QualificationsBachelor's in Data Science, Statistics, Computer Science, Engineering, Mathematics or Economics (Master's preferred).About Company:PARK Management Consultants is a management and technology advisory firm specializing in Product, Asset, Resource and Knowledge Management. We help organizations optimize resources, strengthen operations and scale with confidence by combining strategic consulting, AI & Machine Learning, digital marketing, UX/UI, design and technology solutions. Our approach brings structure, clarity and sustainable growth to complex business environments.

Responsibilities

About the Role

We're building a next-generation online property marketplace, connecting buyers, renters, sellers and agents through listings, search, valuations and market insights. You'll bridge business, product and engineering, defining what to measure and building the AI/ML models and data pipelines that power platform features and decisions.

Key Responsibilities

Analytics: Define and track marketplace KPIs (listing volume, engagement, enquiry conversion, agent retention, revenue per listing); build executive and self-serve dashboards; design and evaluate A/B tests.

Requirements: Gather needs from product, sales and marketing stakeholders and translate them into data specifications.

Data engineering: Design data models for listings, properties, suburbs, agents and users; build ETL/ELT pipelines for listing feeds, ABS/census, geospatial and third-party data; ensure quality and compliance with the Privacy Act.

AI/ML: Develop and deploy automated valuation models, recommendations, search ranking, suburb price forecasting, lead scoring and duplicate/fraud detection.

NLP, vision and GenAI: Extract features from listing text and photos; explore semantic search, conversational property search and listing description generation.

MLOps: Work with engineering to productionise models and monitor drift, bias and performance.

Communication: Present insights to non-technical audiences and mentor junior analysts.

Required Skills & Experience

1+ years in data analytics or data science, ideally in marketplace, proptech, e-commerce or classifieds

At least one ML model taken from idea to production

Advanced SQL; Python (pandas, scikit-learn, XGBoost/LightGBM) and/or R

ML fundamentals: regression, classification, clustering, time series, recommenders

BI tools (Tableau, Power BI or Looker) and product analytics (GA4, Amplitude or Mixpanel)

Cloud data stack: AWS/GCP/Azure, Snowflake/BigQuery, dbt, Airflow

Experimentation and statistical testing

Strong stakeholder management and data storytelling; understanding of marketplace dynamics

Desirable

Deep learning (PyTorch/TensorFlow), LLMs, RAG and vector databases

Geospatial analysis (PostGIS, GeoPandas, H3)

MLOps (MLflow, SageMaker/Vertex AI, Docker, CI/CD)

Knowledge of Australian property data (CoreLogic/Cotality, PropTrack, ABS, land registries)

Responsible AI and explainability (SHAP, LIME)