IBM Summer Internship Program!
Position: Research Intern - AI
Qualifications: Bachelorβs Degree
Salary: 30K - 50K Per Month (Expected)
Batch: 2024/ 2025/ 2026/ 2027
Experience: Freshers
Location: Bangalore; Gurgaon, India (Hybrid)
πApply Now: https://ibmglobal.avature.net/en_US/careers/JobDetail?jobId=59041&source=WEB_Search_INDIA
All the best ππ
Position: Research Intern - AI
Qualifications: Bachelorβs Degree
Salary: 30K - 50K Per Month (Expected)
Batch: 2024/ 2025/ 2026/ 2027
Experience: Freshers
Location: Bangalore; Gurgaon, India (Hybrid)
πApply Now: https://ibmglobal.avature.net/en_US/careers/JobDetail?jobId=59041&source=WEB_Search_INDIA
All the best ππ
β€2
  Template to ask for referrals 
(For freshers)
ππ
Hi [Name],
I hope this message finds you well.
My name is [Your Name], and I recently graduated with a degree in [Your Degree] from [Your University]. I am passionate about data analytics and have developed a strong foundation through my coursework and practical projects.
I am currently seeking opportunities to start my career as a Data Analyst and came across the exciting roles at [Company Name].
I am reaching out to you because I admire your professional journey and expertise in the field of data analytics. Your role at [Company Name] is particularly inspiring, and I am very interested in contributing to such an innovative and dynamic team.
I am confident that my skills and enthusiasm would make me a valuable addition to this role [Job ID / Link]. If possible, I would be incredibly grateful for your referral or any advice you could offer on how to best position myself for this opportunity.
Thank you very much for considering my request. I understand how busy you must be and truly appreciate any assistance you can provide.
Best regards,
[Your Full Name]
[Your Email Address]
(For freshers)
ππ
Hi [Name],
I hope this message finds you well.
My name is [Your Name], and I recently graduated with a degree in [Your Degree] from [Your University]. I am passionate about data analytics and have developed a strong foundation through my coursework and practical projects.
I am currently seeking opportunities to start my career as a Data Analyst and came across the exciting roles at [Company Name].
I am reaching out to you because I admire your professional journey and expertise in the field of data analytics. Your role at [Company Name] is particularly inspiring, and I am very interested in contributing to such an innovative and dynamic team.
I am confident that my skills and enthusiasm would make me a valuable addition to this role [Job ID / Link]. If possible, I would be incredibly grateful for your referral or any advice you could offer on how to best position myself for this opportunity.
Thank you very much for considering my request. I understand how busy you must be and truly appreciate any assistance you can provide.
Best regards,
[Your Full Name]
[Your Email Address]
β€4
  company name: JP Morgan Chase
role: sde-1
batch: 2024/23 passouts
link:https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/210667642
  
  role: sde-1
batch: 2024/23 passouts
link:https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/210667642
JPMC Candidate Experience page
  
  Software Engineer I
  Join an agile team that designs and delivers market-leading technology products in a secure and scalable way
  S&P Global is hiring Data Analyst ππ₯ 
Experience : 0-6 Months
Location : Bangalore
Apply link : https://careers.spglobal.com/jobs/319690?lang=en-us&utm_source=linkedin
  
  Experience : 0-6 Months
Location : Bangalore
Apply link : https://careers.spglobal.com/jobs/319690?lang=en-us&utm_source=linkedin
Data Analyst in Bangalore, India | S&P Global
  
  
  S&P Global is hiring a Data Analyst in Bangalore, India. Review all of the job details and apply today!
β€1
  Data Engineering Roadmap for Beginners (2025)
> Language β Python + SQL.
> OS Basics β Linux + Bash + Git.
> Data Modeling β Normalization + Star/Snowflake Schema.
> Databases β PostgreSQL + MySQL + MongoDB.
> Data Warehousing β Snowflake + BigQuery + Redshift.
> Data Processing β Apache Spark + PySpark.
> Workflow Orchestration β Airflow + Prefect.
> Data Lakes β Delta Lake + Apache Hudi + Iceberg.
> Streaming β Kafka + Flink
> Cloud Platforms β AWS (S3, Glue, EMR) / GCP (GCS, Dataflow, BigQuery) / Azure (Data Factory, Synapse).
> Data Quality/Validation β Great Expectations.
> Containerization β Docker + Kubernetes.
> Infra as Code β Terraform.
> Visualization β dbt + Looker/PowerBI/Tableau.
> Language β Python + SQL.
> OS Basics β Linux + Bash + Git.
> Data Modeling β Normalization + Star/Snowflake Schema.
> Databases β PostgreSQL + MySQL + MongoDB.
> Data Warehousing β Snowflake + BigQuery + Redshift.
> Data Processing β Apache Spark + PySpark.
> Workflow Orchestration β Airflow + Prefect.
> Data Lakes β Delta Lake + Apache Hudi + Iceberg.
> Streaming β Kafka + Flink
> Cloud Platforms β AWS (S3, Glue, EMR) / GCP (GCS, Dataflow, BigQuery) / Azure (Data Factory, Synapse).
> Data Quality/Validation β Great Expectations.
> Containerization β Docker + Kubernetes.
> Infra as Code β Terraform.
> Visualization β dbt + Looker/PowerBI/Tableau.
β€5
  β
 Step-by-Step Approach to Learn Data Analytics ππ§ 
β Excel Fundamentals:
β Master formulas, pivot tables, data validation, charts, and graphs.
β SQL Basics:
β Learn to query databases, use SELECT, FROM, WHERE, JOIN, GROUP BY, and aggregate functions.
β Data Visualization:
β Get proficient with tools like Tableau or Power BI to create insightful dashboards.
β Statistical Concepts:
β Understand descriptive statistics (mean, median, mode), distributions, and hypothesis testing.
β Data Cleaning & Preprocessing:
β Learn how to handle missing data, outliers, and data inconsistencies.
β Exploratory Data Analysis (EDA):
β Explore datasets, identify patterns, and formulate hypotheses.
β Python for Data Analysis (Optional but Recommended):
β Learn Pandas and NumPy for data manipulation and analysis.
β Real-World Projects:
β Analyze datasets from Kaggle, UCI Machine Learning Repository, or your own collection.
β Business Acumen:
β Understand key business metrics and how data insights impact business decisions.
β Build a Portfolio:
β Showcase your projects on GitHub, Tableau Public, or a personal website. Highlight the impact of your analysis.
π Tap β€οΈ for more!
β Excel Fundamentals:
β Master formulas, pivot tables, data validation, charts, and graphs.
β SQL Basics:
β Learn to query databases, use SELECT, FROM, WHERE, JOIN, GROUP BY, and aggregate functions.
β Data Visualization:
β Get proficient with tools like Tableau or Power BI to create insightful dashboards.
β Statistical Concepts:
β Understand descriptive statistics (mean, median, mode), distributions, and hypothesis testing.
β Data Cleaning & Preprocessing:
β Learn how to handle missing data, outliers, and data inconsistencies.
β Exploratory Data Analysis (EDA):
β Explore datasets, identify patterns, and formulate hypotheses.
β Python for Data Analysis (Optional but Recommended):
β Learn Pandas and NumPy for data manipulation and analysis.
β Real-World Projects:
β Analyze datasets from Kaggle, UCI Machine Learning Repository, or your own collection.
β Business Acumen:
β Understand key business metrics and how data insights impact business decisions.
β Build a Portfolio:
β Showcase your projects on GitHub, Tableau Public, or a personal website. Highlight the impact of your analysis.
π Tap β€οΈ for more!
β€7