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.
⢠3â8 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.
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