Data Scientist

12 hours ago

Bengaluru, Karnataka, India Neostats Analytics Solutions Full time ₹ 1,04,000 - ₹ 1,30,878 per year

Role & responsibilities

  • Develop and implement statistical models and machine learning algorithms for customer behavior prediction, and product optimization.
  • Analyze large-scale structured and unstructured data using Python, SQL, Databricks and other data tools.
  • Partner with business stakeholders to define problems, determine analytic approaches, and deliver insights and recommendations.
  • Conduct deep dives into credit card customer behavior to identify opportunities for acquisition, retention, and cross-sell.
  • Design A/B tests and interpret results to guide marketing and product strategies.
  • Work with data engineering teams to ensure scalable and production-ready data pipelines.
  • Knowledge of SAS is preferred.
  • Stay updated on the latest advancements in machine learning and analytics to continuously improve models and methodologies.
  • Collaborate with cross-functional teams to ensure alignment between analytics solutions and business objectives.

Preferred candidate profile

Experience: 6+ years of hands-on experience as a Data Scientist or in a similar analytical role.

Technical Proficiency:

  • Expertise in Python (pandas, numpy, scikit-learn, etc.) for data analysis and modeling.
  • Advanced knowledge of SQL for data extraction, transformation, and manipulation.
  • Solid experience in statistical modeling and machine learning techniques (e.g., regression, decision trees, clustering, XGBoost, SAS is preferred).

Domain Knowledge:

  • Prior experience in banking or financial services, especially in credit card analytics, is mandatory.
  • Strong understanding of business metrics and KPIs in the financial domain.

Additional Skills:

  • Ability to design and interpret A/B tests to guide strategic decisions and for campaign management
  • Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn) is a plus.
  • Excellent communication skills to present technical findings to non-technical stakeholders.

Education:

Bachelor's or masters degree in data science, Statistics, Computer Science, or a related field.

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