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5.0 - 10.0 years

17 - 32 Lacs

Mumbai

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Role & responsibilities Conduct relevant statistical tests to validate hypotheses and ensure data-driven outcomes. Design, develop, and deploy advanced statistical and machine learning models to analyze complex datasets, including those from the a app and other projects. Perform data fusion activities by leveraging techniques to merge, reconcile, and analyze information from disparate systems and formats. Employing modern weighing and projection methods to answer key business questions and predict future trends. Design and manage interactive dashboards using Power BI for real-time data visualization. Perform Exploratory Data Analysis (EDA) to identify patterns, anomalies, and opportunities. Collaborate with product and research teams by providing feedback based on analytical findings. Analyze survey data to extract actionable insights and trends. Define and create Key Performance Indicators (KPIs) based on APP data. Serve as the gatekeeper for data maps, ensuring data integrity and accessibility for stakeholders. Develop and maintain MIS dashboards Mentor the team and improve the overall performance of the team Preferred candidate profile Key skills / Abilities MSc in Statistics or a related quantitative field. Strong experience in statistical analysis, predictive modelling and data validation. Proficiency in Python and Power BI are necessary with experience of working in libraries used for numerical and text analysis such as Pandas, Numpy, PySpark, NLTK, SpaCy, Scikit-Learn, Genism. Experience of working with both parametric and non-parametric methods. Advanced knowledge of survey analytics and EDA techniques. Excellent communication skills for cross-functional collaboration. Experience with MIS dashboard development and KPI creation. High attention to detail and commitment to data quality. Experienced Required Experience working with app-based data and multi-project analytics environments. Familiarity with analyzing multiple survey data. Background in creating and managing KPIs aligned with business objectives. Exposure to big data technologies and cloud-based data platforms. Ability to work collaboratively in cross-functional teams involving product, research, and engineering stakeholders. Must have lead the data science team in past Experience of developing algorithm using combination of Data Science and statistics

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