Hyderabad, Telangana, India
Information Technology
Full-Time
AiDASH
Overview
Responsibilities
- Extract, clean, and analyse large datasets from multiple sources using SQL and Python/R.
- Build and optimise data scraping pipelines to process large-scale unstructured data.
- Perform statistical analysis and data mining to identify trends, patterns, and anomalies.
- Develop automated workflows for data preparation and transformation.
- Conduct data quality checks and implement validation procedures.
- Build and validate ML models (classification, regression, clustering) using TensorFlow, Keras, and Pandas.
- Apply feature engineering to enhance accuracy and interpretability.
- Execute experiments, apply cross-validation, and benchmark model performance.
- Collaborate on A/B testing frameworks to validate hypotheses.
- Work on predictive analytics for wildfire risk detection and storm damage assessment.
- Translate complex business requirements into data science solutions.
- Develop predictive models and analytical tools that directly support CRIS decision-making.
- Create interactive dashboards and automated reports for stakeholders.
- Document methodologies and maintain clean, production-ready code repositories.
- 4-5 years of hands-on experience in data science, analytics, or quantitative research.
- Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related field.
- Strong programming skills in Python for data analysis and machine learning.
- Proficiency in SQL and experience with relational databases.
- Experience with ML libraries (scikit-learn, pandas, NumPy, Keras, TensorFlow).
- Knowledge of statistical methods (clustering, regression, classification) and experimental design.
- Familiarity with data visualisation tools (matplotlib, seaborn, ggplot2 Tableau, or similar).
- Exposure to cloud platforms (AWS, GCP, Azure) is a plus.
- Proven experience with end-to-end model development (from data exploration to deployment).
- Track record of delivering actionable insights that influenced business decisions.
- Strong analytical and problem-solving skills with attention to detail.
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