Data Scientist

Kreditbee; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

KreditBee is hiring a mid-level Data Scientist in Bengaluru to turn data into actionable insights. You will work across analytics, ML, and data engineering to solve business problems and drive decisions with scalable models.

The role emphasizes production-ready ML, feature engineering, and collaboration with cross-functional teams. Strong communication is essential for presenting results to both technical and business stakeholders.

Qualifications

• Bachelor's or Master's in a quantitative field or equivalent.
• Strong programming and ML model development skills.
• Experience with data visualization and storytelling.

Responsibilities

• Analyze large datasets to identify trends and opportunities.
• Build, validate, and deploy ML models for business use cases.
• Create dashboards and visualizations for stakeholders.
• Collaborate with product and engineering teams on data-driven projects.
• Monitor model performance and iterate with experiments.

Skills

Python

SQL

R

ML algorithms

Data visualization

Education

Bachelor's or Master's in Data Science

Tools

Scikit-learn

TensorFlow

PyTorch

XGBoost

Tableau

Power BI

Matplotlib

Seaborn

Job description

Job Title: Data Scientist - Analytics & Machine Learning

We are seeking a talented and analytical Data Scientist to join our growing AI and Analytics team. In this role, you will leverage statistical analysis, machine learning, and data engineering techniques to solve complex business problems and deliver actionable insights. You will work closely with cross-functional teams to develop predictive models, optimize business processes, and build scalable data-driven solutions that influence strategic decision-making.

The ideal candidate combines strong analytical thinking with hands-on experience in machine learning, data visualization, and programming, along with the ability to communicate complex findings to both technical and non-technical stakeholders.

What You'll Do

Data Analysis & Business Insights

• Analyze large, structured, and unstructured datasets to identify trends, patterns, and business opportunities.
• Perform exploratory data analysis (EDA) and statistical analysis to uncover actionable insights.
• Translate analytical findings into business recommendations that support strategic decision-making.
• Collaborate with business stakeholders to define key metrics and performance indicators.
• Develop, train, validate, and deploy machine learning models for classification, regression, forecasting, clustering, and recommendation systems.
• Build predictive and statistical models to solve business challenges across multiple domains.
• Optimize model performance through feature engineering, hyperparameter tuning, and model evaluation.
• Continuously monitor model performance and improve prediction accuracy.
• Design efficient data pipelines for data extraction, transformation, and preparation.
• Automate data processing and analytical workflows to improve operational efficiency.
• Ensure data quality, consistency, and reliability across analytical solutions.
• Work with engineering teams to integrate machine learning models into production systems.
• Develop dashboards, reports, and interactive visualizations using modern BI tools.
• Present analytical insights through compelling visual storytelling for technical and business audiences.
• Monitor business KPIs and provide regular performance reporting.

Cross-Functional Collaboration

• Partner with product, engineering, marketing, finance, and business teams to deliver data-driven solutions.
• Work closely with stakeholders to understand business problems and translate them into analytical use cases.
• Support experimentation, A/B testing, and hypothesis-driven decision-making across the organization.
• Stay current with advancements in machine learning, artificial intelligence, and analytics.
• Evaluate new algorithms, tools, and technologies to improve analytical capabilities.
• Contribute to the development of scalable AI and data science best practices.

What We're Looking For

Educational Background

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related quantitative field.

Technical Expertise

• Strong proficiency in Python, SQL, and R for data analysis and machine learning.
• Hands-on experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.
• Strong understanding of statistics, probability, predictive modeling, and experimental design.
• Experience with data visualization tools such as Tableau, Power BI, Matplotlib, or Seaborn.
• Knowledge of data wrangling, feature engineering, and model evaluation techniques.

Professional Experience

• 2+ years of experience in Data Science, Machine Learning, or Analytics.
• Experience working with structured and unstructured datasets at scale.
• Proven ability to develop and deploy machine learning models in production environments.
• Strong analytical, problem-solving, and communication skills.

Nice to Have

• Experience with AWS, Microsoft Azure, or Google Cloud Platform.
• Familiarity with Spark, Hadoop, Databricks, or distributed data processing frameworks.
• Experience working with data warehouses and modern data platforms.

Advanced AI & Analytics

• Experience with Natural Language Processing (NLP), Computer Vision, or Deep Learning.
• Knowledge of Large Language Models (LLMs), Generative AI, or Retrieval-Augmented Generation (RAG).
• Experience with recommendation systems, time-series forecasting, or optimization algorithms.
• Understanding of MLOps, model deployment, monitoring, and CI/CD pipelines.

Business & Communication

• Experience translating business problems into data science solutions.
• Strong stakeholder management and presentation skills.
• Ability to communicate technical concepts clearly to business audiences.

Tools & Technologies

• Programming: Python, SQL, R
• MLOps & DevOps: MLflow, Docker, Git, Airflow, CI/CD

Why You'll Love Working With Us

• Opportunity to work on innovative AI, machine learning, and analytics projects.
• Exposure to cutting-edge technologies including Generative AI and predictive analytics.
• Collaborative and growth-focused engineering culture.
• Continuous learning, mentorship, and career development opportunities.
• Competitive compensation and benefits.

Position: Data Scientist

Employment Type: Full-Time

Experience Level: Mid-Level (2+ Years)

This job description is intended to outline the general nature and key responsibilities of the position. It is not intended to be an exhaustive list of all duties, responsibilities, or qualifications associated with the role. The responsibilities and qualifications described may be subject to change, and other duties may be assigned as needed. Employment is at-will, meaning the employee or the employer may terminate the employment relationship at any time, with or without cause, and with or without notice.

By applying for this position, you acknowledge and agree that any personal data you provide may be used for recruitment and employment purposes. The data collected will be stored and processed in accordance with our privacy policy and applicable data protection laws. Your information will only be shared with relevant internal stakeholders and will not be disclosed to third parties without your consent, unless required by law.