Job Description:
We are seeking a talented and analytical Data Scientist to join our team and transform complex data into actionable insights that drive strategic decisions. The ideal candidate will have hands-on experience in data analysis, statistical modeling, and machine learning, with the ability to interpret large datasets to uncover trends, patterns, and opportunities.
As a Data Scientist, you will collaborate with business stakeholders, data engineers, and software developers to design and implement data-driven solutions that improve operational efficiency, optimize processes, and support business growth. You will develop predictive models, perform exploratory data analysis, and create visualizations to communicate insights effectively to both technical and non-technical audiences.
This role requires strong analytical skills, proficiency in programming, and expertise in statistical and machine learning methods. The Data Scientist will contribute to the development of advanced analytics platforms, automated reporting systems, and data-driven products that support innovation across the organization.
Responsibilities:
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Collect, clean, and preprocess structured and unstructured data from multiple sources.
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Perform exploratory data analysis (EDA) to identify trends, anomalies, and correlations.
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Develop predictive, classification, and clustering models using machine learning techniques.
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Collaborate with data engineers to optimize data pipelines and ensure data quality.
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Create dashboards, reports, and visualizations to communicate insights effectively.
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Implement statistical tests and hypothesis-driven analysis for business decision support.
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Optimize machine learning models for performance, scalability, and deployment.
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Work with cross-functional teams to identify business problems and design analytical solutions.
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Stay updated on emerging data science methodologies, tools, and best practices.
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Document workflows, models, and processes to ensure reproducibility and maintainability.
Preferred Qualifications:
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Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or related field.
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Proficiency in Python, R, SQL, and associated libraries for data analysis (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
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Strong knowledge of statistical modeling, machine learning, and predictive analytics.
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Experience with data visualization tools like Tableau, Power BI, or Matplotlib/Seaborn.
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Understanding of data warehousing, ETL processes, and big data technologies (Hadoop, Spark, or similar).
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Familiarity with cloud platforms (AWS, Azure, Google Cloud) and deploying ML models.
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Strong analytical, problem-solving, and critical-thinking skills.
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Excellent communication skills to convey technical insights to non-technical stakeholders.
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Ability to work in a fast-paced, collaborative environment managing multiple projects.