Data Science Intern (Risk Analytics, Data Ops & Automation)

0 - 1 years

0 Lacs

Posted:4 hours ago| Platform: Naukri logo

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Job Type

Internship

Job Description

Data Science Intern (Risk Analytics, Data Ops & Automation)

Location:

About

IoT, telematics, advanced analytics, machine learning, GenAI, and workflow automation

Role Overview

Data Science Intern

Key Responsibilities

1. Risk Analytics

  • Assist in statistical analysis and exploratory data analysis (EDA) across large telematics datasets.
  • Conduct pattern recognition and anomaly detection for fuel, GPS, OBD, and video analytics data.

2. Data Annotation &

  • Maintain labelling quality benchmarks and annotation consistency at scale.
  • Work with automated labelling tools and create/maintain labelling SOPs.

3. Data Pipelines & Engineering Support

  • Work with senior engineers to document ETL flows and implement workflow automations.
  • Contribute to data quality checks (DI/DQM) and metadata documentation.

4. Business Intelligence & Automation

  • Support end-to-end workflow automation for analyticsalerting, reporting, and monitoring flows.
  • Prepare storyboards and insight summaries for leadership and customers.

Expected Hard Skills

  • Python

    (Pandas, NumPy, basic ML, automation scripts)
  • SQL

    (joins, aggregations, window functions)
  • Statistics

    (hypothesis testing, distributions, correlation, regression)
  • Data Visualization

    (Power BI, Tableau, Matplotlib/Plotly)
  • Understanding of data cleaning, preprocessing, feature engineering
  • Basic knowledge in machine learning is a plus

Expected Soft Skills

  • Proactive & self-starter mindset

  • Strong

    communication

    skills
  • Ability for

    storyboarding

    insights and presenting structured outputs
  • Curiosity and hunger to learn

  • Ability to go the

    extra mile

    and work in ambiguous fast-paced environments
  • High ownership and strong attention to detail

Learning & Exposure You Will Get

During this internship, you will work directly with product, engineering, and data science leadership and gain exposure to:

  • IoT, telematics & sensor data (GPS, OBD, fuel, video)

  • SaaS product engineering & analytics workflows

  • AI, ML & GenAI applications

    in real-world fleet & logistics
  • Data engineering

    , pipeline development & end-to-end DI/DQM
  • Optimization models

    and predictive analytics
  • Workflow automation frameworks

  • How modern

    fleet,

    logistics

    & transportation

    ecosystems operate
  • Working in a

    high-growth, fast-paced startup

    environment

Who Should Apply

  • Students or recent graduates in engineering, statistics, mathematics, computer science, or related fields
  • Individuals passionate about AI, data science, IoT, transportation analytics, and solving real-world industry challenges
  • People who want hands-on experience in building practical, scalable data products

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