Senior Data Scientist responsible for analyzing large datasets, building predictive and statistical models (fraud, risk, customer analytics), conducting EDA and A/B testing, creating dashboards, and communicating insights. Collaborates with product, engineering, and operations to improve decision-making, automation, and regulatory/compliance analytics; documents methodologies for scalability.
This role is for one of the Weekday's clients
Salary range: Rs 2000000 - Rs 5000000 (ie INR 20-50 LPA)
Min Experience: 5 years
Location: Pune
JobType: full-time
We seek a Senior Data Scientist who is highly analytical and business-oriented, with extensive experience in addressing complex business challenges through data-driven methods. This hands-on individual contributor position emphasizes extracting insights, developing predictive models, performing advanced analytics, and supporting strategic decision-making within fintech and regulatory technology contexts.
The ideal candidate will possess strong expertise in statistical analysis, predictive modeling, experimentation, and the ability to transform large datasets into practical business insights.
Requirements
Key Responsibilities:
- Examine extensive structured and unstructured datasets to uncover trends, patterns, anomalies, and business opportunities.
- Develop predictive and statistical models for various applications including fraud detection, risk scoring, customer analytics, behavioral analysis, and optimizing operations.
- Conduct exploratory data analysis (EDA), hypothesis testing, feature engineering, and model assessment.
- Create analytical frameworks and dashboards to aid business and product decision-making.
- Collaborate closely with product, business, operations, and engineering teams to address high-impact business challenges using data.
- Derive actionable insights from customer behavior, transaction data, and operational metrics.
- Design and execute experiments, A/B testing frameworks, and performance evaluation methodologies.
- Prepare data-driven storytelling presentations and effectively communicate analytical results to both technical and non-technical audiences.
- Enhance data quality, interpretation, and analytical processes across various teams.
- Document methodologies, assumptions, and analytical workflows to ensure scalability and future reference.
Key Problem Areas:
- Fraud analysis and anomaly detection.
- Customer behavior examination and trust/risk scoring.
- Predictive analytics aimed at improving operational efficiency and automation.
- Analytics related to claims and insurance.
- Intelligent document analytics and classification insights.
- NLP-based text analytics and contract intelligence.
- Business forecasting and trend analysis.
- Compliance and regulatory analytics.
Key Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, Economics, or a related discipline.
- Over 5 years of practical experience in data science, analytics, or statistical modeling roles.
- Strong analytical and problem-solving abilities demonstrated by addressing real-world business issues.
- Experience in fintech, SaaS, analytics consulting, or data-driven product companies is preferred.
Technical Skills:
- Expertise in Python and analytical libraries such as Pandas, NumPy, Scikit-learn, Statsmodels, or SciPy.
- Solid understanding of statistics, probability, machine learning principles, and predictive analytics.
- Practical experience with SQL and performing large-scale data analyses.
- Familiarity with data visualization and BI tools like Tableau, Power BI, or Looker.
- Knowledge of machine learning techniques including classification, regression, clustering, and forecasting.
- Preferred exposure to cloud platforms such as AWS, GCP, or Azure.
- Experience with big data technologies like Spark is an advantage.
- Preferred familiarity with NLP, text analytics, or behavioral analytics.
- Excellent communication and stakeholder management skills, with the ability to present insights clearly.
predictive modeling, Fraud/Risk Analytics, Python + SQL, Machine Learning
Good-to-have skillsPandas, python pandas
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