Data Scientist (Machine Learning) - Part-Time

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.