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Data Scientist (Machine Learning)
Job Location:
Monthly Salary:
Experience Required:
Posted:
10 July 2026 (30+ days ago)
Posted:
Application Deadline:
7 October 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
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
Bachelors or Masters degree in Data Science Computer Science Statistics Mathematics Engineering or a related discipline.
38 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.
Required Skills:
Data Scientist (Machine Learning)
Required Education:
degree / diploma
