Entry-Level Data Analyst

I’m helping

bEdge Tech Services

find a top candidate to join their team

full-time

for the role of

Entry-Level Data Analyst

.

You'll drive data-driven decisions by building predictive models and actionable insights.

Compensation:

USD 72K - 93K/year

Location:

Remote: United States

Mission of bEdge Tech Services:

"To empower global businesses with exceptional talent and innovative technology solutions while creating meaningful opportunities for professionals. We are committed to delivering value, driving growth, and building lasting connections that fuel success."

What makes you a strong candidate:

• You are proficient in Statistics, SQL, Python, Pandas, NumPy, Monitoring, Machine learning.
• You have the potential to develop in Tableau, Cloud platforms.
• English - Conversational

Responsibilities and more:

Job Summary:

• We are seeking a motivated Entry-Level Data Scientist to support data-driven decision-making by analyzing datasets, building basic predictive models, and generating insights.

• This role is ideal for recent graduates or candidates with 0–2 years of experience who are passionate about data, statistics, and machine learning.

Key Responsibilities:

• Collect, clean, and preprocess structured and unstructured data.

• Perform exploratory data analysis (EDA) to identify trends and patterns.

• Build and evaluate basic machine learning models.

• Develop data visualizations and dashboards.

• Write SQL queries to extract and validate data.

• Collaborate with data engineers, analysts, and business teams.

• Document methodologies, findings, and model results.

• Support deployment and monitoring of models (basic level).

Required Skills \& Qualifications:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.

• 0–2 years of experience (freshers welcome).

• Strong knowledge of Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn).

• Strong knowledge of statistics and probability (hypothesis testing, distributions).

• Strong knowledge of SQL (joins, aggregations).

• Basic understanding of machine learning algorithms.

• Strong analytical and problem-solving skills.

• Good communication skills.

Preferred Qualifications:

• Internship or academic project in data science or analytics.

• Experience with tools such as Jupyter Notebook.

• Experience with tools such as Power BI or Tableau.

• Exposure to deep learning (TensorFlow or PyTorch).

• Exposure to cloud platforms (AWS, Azure, GCP).

• Knowledge of data pipelines or big data tools (Spark – basic).

Key Deliverables:

• Cleaned datasets and data pipelines (basic level).

• Data analysis reports and dashboards.

• Machine learning models (baseline models).

• Documentation of insights and recommendations.

Your potential leader(s):

• Chirag Panchal -