Junior Data Scientist

3 years

0 Lacs

Posted:11 hours ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do?


AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics.


Do You Dream Big?


We Need You.



Job Title:

Location:

Reporting to:



1. Purpose of Role


The Junior Data Scientist will support the development of analytical solutions that enable data-driven decision-making across the organization. The role focuses on building foundational skills in Python, SQL, and core data science workflows. It involves working closely with senior team members to prepare data, develop basic models, perform exploratory analysis, and contribute to documentation and reproducibility. This position is designed for individuals who can learn quickly, collaborate effectively, and apply structured problem-solving to business challenges.


2. Key Tasks and Accountabilities


  • Assist in developing data science models and analytical components using Python with working knowledge of syntax, data structures, and foundational libraries such as pandas and numpy
  • Conduct exploratory data analysis, basic feature creation, and initial statistical checks under the guidance of senior team members
  • Write clean, readable, and well-organized code while following best practices shared by the team
  • Collaborate with cross-functional teams to understand data needs, gather requirements, and support translation of business questions into analytical tasks
  • Work with existing codebases to understand workflow logic, make incremental enhancements, and support maintenance tasks
  • Use version control tools like Git for basic code commits, branching, and collaboration.
  • Write simple to intermediate SQL queries to extract and prepare data from relational databases
  • Support documentation of processes, datasets, code logic, and outputs for future use
  • Learn and adopt standard development and data science methodologies including model evaluation, reproducibility, and simple automation of tasks
  • Participate in team learning initiatives, staying curious about new tools, techniques, and best practices in analytics


3. Qualifications, Experience and Skills


Education:


  • Bachelor’s degree in computer science, Information Systems, Mathematics, Statistics, Engineering, or a related discipline.


Experience:


  • 1–3 years of experience in data science, analytics, or related technical roles, preferably with exposure to hands-on projects, internships, or academic assignments involving Python and data analysis.


Mandatory Skills:


  • Python Programming (Beginner to Intermediate):

  • Basic proficiency with syntax, data structures, and use of core libraries such as pandas and numpy.
  • Data Science Foundations:

  • Understanding of descriptive statistics, basic model-building concepts, and feature preparation.
  • SQL (Beginner to Intermediate):

  • Ability to write queries for data extraction and manipulation.
  • Version Control (Git):

  • Familiarity with commits, branches, and collaborative code workflows.
  • Code Adaptability:

  • Ability to read and understand existing code and make minor enhancements.


Preferred (Good to Have) Skills


  • Exposure to Object-Oriented Programming (OOP) concepts in Python
  • Basic knowledge of model evaluation techniques or lifecycle stages
  • Awareness of test-driven development principles
  • Experience with Jupyter notebooks, dashboards, or simple automation scripts.



And above all of this, an undying love for beer!

We dream big to create future with more cheers.

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