Bangalore, Karnataka, India
Information Technology
Other
LenDenClub
Overview
About the Role
We are looking for a results-driven Data Scientist with 2–5 years of experience to join our growing AI Innovation Hub team. In this role, you will extract insights from data, develop predictive models, and help shape data-driven strategies that directly impact the business. You’ll work on a variety of projects ranging from exploratory data analysis to building production-grade ML models in collaboration with engineering and product teams.
Key Responsibilities
Analyze large, complex datasets to uncover actionable insights and trends.
Design, develop, and deploy machine learning models for classification, regression, clustering, or recommendation use cases.
Translate business problems into analytical frameworks and solutions.
Perform feature engineering, model selection, hyperparameter tuning, and performance evaluation.
Communicate findings clearly through visualizations, dashboards, and presentations to both technical and non-technical stakeholders.
Collaborate with data engineers and ML engineers to productionize models and ensure data pipeline integrity.
Conduct A/B tests and experiments to validate hypotheses and measure impact.
Contribute to the development of a centralized knowledge base for data science solutions, reusable code, and templates.
Stay current with advances in data science, machine learning, and statistics.
Required Qualifications
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
2–5 years of professional experience in data science or a related role.
Proficient in Python and data science libraries such as Pandas, NumPy, scikit-learn, XGBoost, and/or TensorFlow/PyTorch.
Strong analytical and statistical skills, including regression, classification, hypothesis testing, and clustering.
Experience with SQL and working with relational or non-relational databases.
Hands-on experience with data visualization tools (e.g., Matplotlib, Seaborn, Plotly, Power BI, or Tableau).
Experience building end-to-end ML workflows and working with version control systems like Git.
Preferred Qualifications
Familiarity with MLOps tools and practices (e.g., MLflow, DVC, Airflow).
Experience with cloud platforms such as AWS, GCP, or Azure.
Understanding of data warehousing and big data technologies (Spark, Hadoop, BigQuery, Redshift).
Background in a domain like fintech, healthtech, e-commerce, or marketing analytics.
Experience with experimentation and causal inference techniques.
Benefits
Competitive salary with annual performance bonuses
Health insurance
Professional development opportunities (conferences, courses, certifications)
Collaborative, high-impact work culture
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