Associate Data Scientist

Job Overview

Role: Associate Data Scientist Location: Bangalore Experience: 0 – 1 Year Qualification: B.E/B.Tech/M.E/M.Tech/B.Sc/M.Sc/BA/MA in Engineering or a quantitative discipline Key Skills: Data Science, Analytics, Machine Learning, Python, SQL, PySpark, Databricks, Data Visualization, Statistical Modelling

Job Description

The Associate Data Scientist at Epsilon will work with business stakeholders and experienced analytics professionals to design and develop analytical solutions. The role involves working with large volumes of customer and third-party data to identify meaningful patterns, generate insights, and support business decisions. You will have the opportunity to work with technologies including Python, SQL, PySpark, Databricks, and modern data platforms. The position also involves statistical analysis, machine learning, data quality checks, visualization, and communicating findings to both technical and non-technical audiences.

Roles and Responsibilities

• Solution Design: Work with business stakeholders and experienced colleagues to design and develop analytics solutions.
• Data Analysis: Use strong problem-solving skills to analyze data and uncover actionable business insights.
• Platform Work: Work with enterprise data systems such as Databricks and other large-scale data platforms.
• Vector Datastores: Learn and work with vector datastore technologies such as FAISS and ChromaDB.
• Scalable Solutions: Build scalable analytical solutions for processing and analyzing large volumes of data.
• Programming: Use Python and SQL for data processing, analysis, and analytical solution development.
• First-Party Data: Perform hands-on analysis of customer first-party data and third-party data.
• Statistical Modelling: Apply statistical and modelling techniques to produce quality and statistically valid analysis.
• Machine Learning: Design and implement machine learning models using Databricks and Python/PySpark.
• Quality Control: Perform quality control of data and analytical results produced by data scientists and junior team members.
• Visualization & Communication: Create meaningful data visualizations and PowerPoint presentations based on analytical findings; communicate statistical results clearly to technical and non-technical audiences.
• Project Management: Take an active role in analysis design, project planning, and execution.
• Status Reporting: Communicate workload and assignment status proactively with supervisors.
• Continuous Learning: Stay updated with new tools, technologies, algorithms, and data science methodologies.
• Collaboration: Collaborate with cross-functional internal teams to deliver analytical solutions.

Skills and Eligibility Criteria

Educational Background: Bachelor's or Master's degree in Engineering or another quantitative discipline such as Statistics, Economics, or Mathematics. Eligible Degrees: B.E, B.Tech, M.E, M.Tech, B.Sc, M.Sc, BA, or MA.

Experience: 0–1 years of experience.

Mandatory Technical Skills:

• Quantitative Skills: Strong aptitude in quantitative analysis and logical reasoning.
• Analytical Thinking: Strong analytical thought process and problem-solving ability.
• Programming: Interest or familiarity with Python and SQL.
• Data Science: Interest in machine learning, statistical modelling, and data analysis.
• Big Data: Willingness to learn platforms such as Databricks and enterprise data systems.
• PySpark: Interest in using Python/PySpark for scalable data processing and machine learning.

Competencies:

• Analytics Tools: Curiosity to learn tools such as SAS, SQL, Python, R, Google Analytics, Adobe Analytics, and MS Office.
• Communication: Ability to explain analytical findings clearly to technical and non-technical audiences.
• Soft Skills: Collaborative attitude, curiosity, motivation, interpersonal skills, and willingness to learn.