Data Scientist (Machine Learning)

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Description

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.

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