Job Description

🎯 Core Responsibilities Explained

1️⃣ Business Requirements → Technical Solutions

• Meet stakeholders
• Understand business problems
• Convert them into data/analytics solutions

This is a very important skill called business translation.

2️⃣ Data Extraction & Processing

Tools mentioned:

• SQL databases
• Tableau data sources
• Data mining and preprocessing

Typical work:

• Query data
• Clean data
• Handle missing values
• Prepare datasets for modeling

3️⃣ Machine Learning / AI

They expect:

• Applying ML algorithms
• Building prototypes
• Testing models

Likely models:

• Classification
• Regression
• Forecasting
• Clustering

Since experience requirement is low, expectations will be moderate.

4️⃣ Data Engineering Exposure

Important part of this role:

• Python ETL pipelines
• Data processing workflows
• Data delivery systems

This is valuable because it combines:

👉 Data Science + Data Engineering

5️⃣ Work Under Supervision

Meaning:

• You will not lead projects yet
• You’ll support senior data scientists
• Learning environment role

Good for career growth.

🎓 Education Requirement Interpretation

They accept:

• Computer Science
• IT
• Engineering (any)
• Business / Analytics related

With:

👉 Master’s degree + 6 months experience

This requirement is common for consulting companies or visa-sponsored roles.

💼 Experience Requirement Reality

Minimum:

• 6 months with Python or Data Science tools

But realistically they prefer:

• Internship
• Academic projects
• Research work
• Capstone projects
• Kaggle / portfolio projects

⚠️ Important Line — Travel / Relocation

“Travel and/or relocation to unanticipated client sites required”

This strongly suggests:

This job is likely from a consulting or IT services company.

Meaning:

• You may move between projects
• Client locations may change
• Could involve onsite assignments

📊 Seniority Level

Equivalent to:

• Junior Data Scientist
• Associate Data Scientist
• Data Analyst with ML
• Entry Data Scientist

💰 Typical Salary Range (US Market)

If this is in the United States:

• $65,000 — $95,000 (entry level consulting)
• Up to $110,000 in strong markets

🚀 Skills That Will Make You Competitive

If you want to qualify easily, focus on:

Must Have

• Python (Pandas, NumPy, Scikit-learn)
• SQL
• Data cleaning
• Machine learning basics
• Data visualization

Strong Advantage

• ETL pipelines
• Cloud (AWS)
• Tableau / Power BI
• Git

⭐ Career Growth Path

This role can lead to:

• Data Scientist
• Machine Learning Engineer
• Senior Data Scientist
• AI Engineer
• Data Engineer

Within 2–4 years with good experience.

✅ Resume Tip (Very Important)

For this role, employers want to see:

• Projects using Python
• SQL queries
• ML models
• Data pipelines
• Business problem solving