Senior Data Scientist - FinBox

Finbox

8 - 13 years

25 - 35 Lacs

bengaluru

Posted:None| Platform:

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Skills Required

automation data analysis product engineering version control machine learning open source analytics financial services sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

How You'll Contribute:

Data Analytics & Insights:
Analyze large datasets to generate meaningful insights and measure business impact.
Model Development & Experimentation:
Design and deploy predictive models, leveraging statistical and machine learning techniques to drive business growth.
Algorithm Development:
Create and optimize algorithms to extract and process data, improving decision-making processes.
Experimentation & A/B Testing:
Conduct rigorous experimentation to refine products and optimize business strategies.
Visualization & Reporting:
Build dashboards and automated reports using visualization tools to communicate insights effectively.
End-to-End Data Processing:
Gather, clean, and pre-process data for insight generation and model building.
Stakeholder Collaboration:
Work closely with product, engineering, and business teams to translate informal requirements into problem statements and solutions.
Model Deployment:
Deploy ML models and ensure they are optimized for production and business applications.

Who You Are:

8+ years of experience
in data science, with a strong background in the finance or fintech sector.
Working experience at a
Banks/NBFCs
will be preferred.
Expertise in Python/R, SQL, and Excel
for data analysis, modeling, and automation.
Proficiency in AWS & Git
for cloud-based deployment and version control.
Strong knowledge of statistical methods and machine learning techniques,
including regression, clustering, decision trees, bootstrapping, and survival analysis.
Hands-on experience with data visualization tools
such as Tableau, Power BI, or open-source libraries.
Strong problem-solving and communication skills
to simplify complex models and insights for business stakeholders.
Experience in deploying data science solutions at scale,
with a focus on automation and real-time analytics.

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