Benefits : 13th Month Salary

About the Role

We are seeking a Data Scientist (Machine Learning) to develop and deploy advanced analytics and machine learning solutions that support business operations and digital transformation initiatives. The successful candidate will work closely with cross-functional teams to analyze large datasets, build predictive models, and deliver actionable insights to improve operational efficiency and business performance.

Key Responsibilities

Develop, train, validate, and deploy machine learning models for predictive analytics and optimization.

Analyze structured and unstructured datasets to identify trends, patterns, and business opportunities.

Design and implement data pipelines for data collection, cleansing, feature engineering, and model training.

Build forecasting, classification, regression, clustering, and anomaly detection models.

Collaborate with business stakeholders to understand requirements and translate them into data-driven solutions.

Evaluate model performance and continuously improve model accuracy and reliability.

Develop dashboards and reports to communicate insights and recommendations.

Work with data engineers to integrate machine learning models into production systems.

Ensure data quality, governance, and compliance with organizational standards.

Research and evaluate new machine learning algorithms and emerging technologies.

Requirements

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related discipline.

3–8 years of experience in Data Science, Machine Learning, or Advanced Analytics.

Strong programming skills in Python (Pandas, NumPy, Scikit-learn).

Experience with machine learning frameworks such as TensorFlow, PyTorch, or XGBoost.

Strong knowledge of supervised and unsupervised learning techniques.

Experience with SQL and relational databases.

Familiarity with cloud platforms such as AWS, Azure, or GCP.

Experience with data visualization tools such as Power BI or Tableau.

Knowledge of Git, Docker, and MLOps concepts is an advantage.

Strong analytical, problem-solving, and communication skills.

Preferred Skills

Experience in time-series forecasting and predictive maintenance.

Knowledge of optimization techniques and operations research.

Experience with big data technologies such as Spark or Hadoop.

Familiarity with Generative AI and Large Language Models (LLMs) is a plus.

Experience working in the utilities, energy, manufacturing, or industrial sectors is highly desirable.

Key Competencies

Strong analytical and statistical thinking.

Ability to communicate complex technical concepts to non-technical stakeholders.

Excellent problem-solving and critical thinking skills.

Self-motivated with the ability to work independently and in a collaborative team environment.

Strong stakeholder management and project delivery skills.