Data Scientist

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