Principle Scientist (Data Analytics)

Biocon Biologics; Johor; On-site; MYR 60,000 - 90,000; Full time

Job summary

A leading biotechnology company in Malaysia is looking for a skilled Data Scientist to join its analytics team. The ideal candidate will have 2–3 years of experience in machine learning and applied statistics, with a solid foundation in statistical analysis and model development. Responsibilities include designing ML models, data preparation, and collaborating with stakeholders to provide data-driven solutions. A Bachelor’s or Master’s degree in a relevant field and proficiency in Python are required. Competitive compensation and opportunities for growth are offered.

Qualifications

• 2–3 years of hands-on experience in machine learning and applied statistics.
• Strong programming skills in Python; working knowledge of SQL.
• Solid foundation in statistics, including probability theory, hypothesis testing.

Responsibilities

• Design, build, and evaluate supervised and unsupervised ML models.
• Clean, preprocess, and transform large datasets from structured and unstructured sources.
• Deploy ML models into production and monitor their performance.
• Translate business problems into statistically sound solutions.

Skills

Machine Learning

Statistical Analysis

Data Preparation

Model Deployment

Data Visualization

Communication

Education

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

Tools

Python

NumPy

pandas

SciPy

scikit-learn

XGBoost

TensorFlow

PyTorch

Flask

FastAPI

Git

Jupyter notebooks

MLflow

DVC

Job description

Job Summary

We are seeking a skilled and motivated Data Scientist with 2–3 years of hands-on experience in machine learning and applied statistics to join our growing analytics team. The ideal candidate will have a strong foundation in statistical analysis, ML algorithms, model development, and deployment, with a passion for solving real‑world problems using data‑driven and statistically sound approaches.

Responsibilities

• Machine Learning & Statistical Modeling: Design, build, and evaluate supervised and unsupervised ML models (e.g., regression, classification, clustering, recommendation systems).
• Data Preparation, EDA & Statistical Analysis: Clean, preprocess, and transform large datasets from multiple structured and unstructured sources.
• Model Evaluation, Deployment & Monitoring: Deploy ML models into production using tools such as Flask, FastAPI, or cloud‑native services; monitor model performance, data drift, and statistical stability; retrain or recalibrate models as required.
• Collaboration & Communication: Work closely with data engineers, product managers, and business stakeholders to translate business problems into statistically and analytically sound solutions; communicate results, assumptions, and limitations of models clearly to both technical and non‑technical audiences.
• Tools & Technologies: Use Python and libraries such as NumPy, pandas, SciPy, scikit‑learn, XGBoost, TensorFlow, or PyTorch; utilize visualization and analytics tools (Matplotlib, Seaborn, Plotly) for statistical reporting; leverage version control (Git), Jupyter notebooks, and ML lifecycle tools (MLflow, DVC).

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• 3–4 years of experience in building, evaluating, and deploying ML models.
• Strong programming skills in Python; working knowledge of SQL.
• Solid foundation in statistics, including probability theory, hypothesis testing, regression analysis, and experimental design.
• Exposure to cloud platforms (AWS, GCP, or Azure) and MLOps practices is advantageous.
• Excellent analytical thinking, problem‑solving, and communication skills.