Role: Senior Associate Data Analytics
Industry Type: Financial Services
Department: Data Science & Analytics
Employment Type: Full Time, Permanent
Role Category: Data Science & Analytics - Other
UG: Any Graduate
PG: Any Postgraduate
- Bachelor or Master degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
- 36 years of hands-on experience in the Data Science domain, with a strong track record of solving real-world business problems using data.
- Experience working in cross-functional environments, collaborating with business stakeholders, product teams, and engineering teams.
- Core Technical Skills Strong understanding of data science fundamentals, including data structures, algorithms, statistical modeling, and database systems.
- Advanced proficiency in SQL for complex querying, data manipulation, and performance optimization.
- Strong programming skills in Python, including experience with libraries such as Pandas, NumPy, Scikit-learn, and other relevant frameworks.
- Machine Learning Advanced Analytics Extensive experience in building, evaluating, and deploying machine learning models in production environments.
- Expertise in feature engineering, model selection, hyperparameter tuning, and performance monitoring.
- Solid understanding of supervised and unsupervised learning techniques, as well as exposure to advanced methods such as time series forecasting, NLP, or deep learning.
- Strong grounding in statistical analysis, hypothesis testing, and experimental design (A/B testing) to derive actionable insights.
- Data Engineering Systems Knowledge Working knowledge of distributed computing frameworks (e.g., Apache Spark) and large-scale data processing systems.
- Experience in designing and maintaining data pipelines, ETL processes, and data transformation workflows.
- Familiarity with cloud platforms such as Azure, AWS, or GCP and exposure to MLOps practices, including model deployment and monitoring.
- Visualization Communication Proficiency in data visualization tools such as Tableau, Power BI, or Superset for developing dashboards and reports.
- Ability to translate complex analytical findings into clear, concise, and actionable insights tailored to both technical and non-technical stakeholders.
- Strong communication and storytelling skills to influence decision-making.
- Ownership Leadership Ability to lead end-to-end data science projects, from problem definition and data exploration to model deployment and business adoption.
- Experience mentoring junior team members and contributing to best practices, code quality, and knowledge sharing.
- Strong problem-solving mindset with attention to detail and a focus on delivering business impact.
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