Senior Data Scientist

Talent Monitor Bangalore; Bengaluru; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

Talent Monitor Bangalore is seeking a Data Scientist to drive data-driven decision making. You will collect, cleanse, and analyze datasets, build ML models to address business problems, and present insights through visualizations.

The role emphasises scalable pipelines, cloud services, and stakeholder communication to inform strategic actions. Excellent Python/SQL skills and experience with AWS data services and BI tools are required, with a track record inTurning insights into actionable

Qualifications

• Proficient in Python and SQL for data extraction, cleaning, analysis, automation, and model development.
• Hands-on experience with pandas, NumPy, scikit-learn, and data visualization libraries.
• Good understanding of ML techniques such as regression, classification, clustering, trees, XGBoost/LightGBM.
• Experience with large and complex datasets from multiple sources.
• Strong working knowledge of AWS data services including S3, Athena, Glue, Redshift, RDS, Lambda, IAM, CloudWatch, EventBridge.
• ETL/data pipelines using AWS Glue, Lambda, APIs and cloud storage; SageMaker for model training preferred.
• Feature engineering, data preprocessing, model validation, and performance tracking.
• APIs, webhooks, data quality checks, logging, and production monitoring basics.
• Translate business problems into analytical, ML or automation solutions; strong stakeholder communication.
• Exposure to financial services, lending, marketing analytics, credit risk or customer analytics is a plus.
• GenAI/LLM use cases, prompt engineering, RAG or chatbot analytics will be a plus.

Responsibilities

• Undertaking data collection, preprocessing and analysis
• Building models to address business problems
• Presenting information using data visualization techniques

Skills

Python

SQL

Pandas

NumPy

scikit-learn

Data visualization

ML techniques

Model development

Communication skills

GenAI/LLM awareness

Education

Engineering/ CS/ Economics/ Statistics/ Mathematics

Tools

Power BI

Tableau

Streamlit

Shiny

AWS Glue

AWS Lambda

AWS Redshift

AWS SageMaker

S3

APIs

Job description

Role of Data scientist:

Undertaking data collection, preprocessing and analysis

Building models to address business problems

Presenting information using data visualization techniques

Required Skillsets

• Strong proficiency in Python and SQL for data extraction, cleaning, analysis, automation, and model development.
• Hands-on experience with pandas, NumPy, scikit-learn, and data visualization libraries.
• Good understanding of machine learning techniques such as regression, classification, clustering, decision trees, random forests, XGBoost/LightGBM, and model evaluation.
• Experience working with large and complex datasets from multiple sources.
• Strong working knowledge of AWS data and analytics services, including S3, Athena, Glue, Redshift, RDS, Lambda, IAM, CloudWatch, and EventBridge.
• Experience building or supporting ETL/data pipelines using AWS Glue, Lambda, scheduled jobs, APIs, and cloud storage.
• Familiarity with AWS SageMaker for model training, deployment, experiment tracking, and model monitoring will be preferred.
• Experience in feature engineering, data preprocessing, model validation, and performance tracking.
• Working knowledge of business analytics, funnel analysis, cohort analysis, customer segmentation, campaign performance measurement, and lead scoring.
• Experience with dashboards and reporting tools such as Power BI, Tableau, Streamlit, Shiny, or similar.
• Basic understanding of APIs, webhooks, data quality checks, logging, and production monitoring.
• Ability to translate business problems into analytical, machine learning, or automation solutions.
• Strong communication skills with the ability to explain insights clearly to business and leadership teams.
• Exposure to financial services, lending, marketing analytics, credit risk, or customer analytics will be an added advantage.
• Familiarity with GenAI/LLM use cases, prompt engineering, RAG, or chatbot analytics will be a plus.

Required Skillsets

• Strong proficiency in Python and SQL for data extraction, cleaning, analysis, automation, and model development.
• Good understanding of machine learning techniques such as regression, classification, clustering, decision trees, random forests, XGBoost/LightGBM, and model evaluation.
• Working Knowledge of building or supporting ETL/data pipelines using AWS Glue, Lambda, scheduled jobs, APIs, and cloud storage.
• Familiarity with AWS SageMaker for model training, deployment, experiment tracking, and model monitoring will be preferred.
• Experience in feature engineering, data preprocessing, model validation, and performance tracking.
• Basic understanding of APIs, webhooks, data quality checks, logging, and production monitoring.
• Ability to translate business problems into analytical, machine learning, or automation solutions.
• Strong communication skills with the ability to explain insights clearly to business and leadership teams.
• Exposure to financial services, lending, marketing analytics, credit risk, or customer analytics will be an added advantage.
• Familiarity with GenAI/LLM use cases, prompt engineering, RAG, or chatbot analytics will be a plus.

What do you need to succeed?

Degree in Engineering/ Computer Science/ Economics, Statistics or Mathematics

Data-driven mindset, critical thinking and problem-solving skill

4+ years of experience in analyzing large, multi-dimensional data sets

Expertise in converting insights into actionable solutions

Expertise in SQL, Excel, and visualization tools such as Power bi, Tableau

Experience with a statistical programming language like Python preferred

Machine learning experience of 4+years of implementing and successfully deploying ML solutions at scale for real-world problems.

Strong written and verbal communication skills to influence stakeholders