Junior Data Analyst

About the Role We are looking for a Data Analyst with strong analytical skills and hands‑on experience in machine learning to join our growing team. In role, you will turn complex data into actionable insights, build predictive models, and support data‑driven decision‑making across the. You’ll collaborate closely with cross‑functional teams to identify business opportunities, design analytical solutions, and drive innovation using data and AI.

Key Responsibilities Data Analysis & Reporting

Collect, clean, and analyze structured and unstructured data from various sources.

Develop dashboards, reports, and visualizations to present insights and business performance metrics.

Identify trends, patterns, and correlations that drive strategic decisions.

Machine Learning & Predictive Modeling

Build and deploy machine learning models (e.g., regression, classification, clustering, recommendation systems) to solve business problems.

Evaluate model performance and continuously optimize for accuracy and scalability.

Collaborate with data engineers to integrate ML models into production environments.

Business Insights

Work with stakeholders to define analytical requirements and translate them into actionable data solutions.

Support experimentation, A/B testing, and forecasting activities.

Communicate complex findings in a clear and concise manner to non‑technical audiences.

Data Governance & Quality

Ensure data accuracy, consistency, and security across platforms.

Develop and maintain documentation for data processes and models.

Qualifications

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

Fresh graduate or 0–1 year of professional experience

as a Data Analyst or related role.

At least one internship experience

in data analytics, data science, business intelligence, or a related field.

Solid proficiency in

Python

(pandas, numpy; basic knowledge of scikit-learn is a plus) and

SQL .

Basic understanding of

statistical analysis, data modeling, and exploratory data analysis (EDA) .

Exposure to

machine learning concepts or projects

(academic or internship-based); hands‑on experience with TensorFlow or PyTorch is a plus.

Experience using

data visualization tools

such as Power BI, Tableau, Looker, or similar tools.

Familiarity with

Git/version control

and basic exposure to

cloud platforms

(AWS, GCP, or Azure) is an advantage.

Strong analytical thinking, problem‑solving skills, and ability to

communicate insights clearly through data storytelling .

Eager to learn, detail‑oriented, and able to work well in a fast‑paced, collaborative environment.

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