Data Scientist 3 4P/298

 

Job Title: Senior Data Scientist

Experience: 10–15 Years
Location: Atlanta, Ga

Contract- 1 Year

Client Southern Company

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Job Summary:

We are seeking a highly experienced and innovative Senior Data Scientist to lead the development and implementation of data-driven solutions across the organization. This strategic role is ideal for a professional with deep technical expertise, strong leadership capabilities, and a proven track record of leveraging advanced analytics and machine learning to solve complex business challenges.

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Key Responsibilities:

• Conduct advanced statistical and machine learning analyses on large, complex data sets

• Develop and deploy predictive models using deep learning, ensemble methods, and neural networks

• Create effective data visualizations using Tableau, Power BI, or Python libraries (Matplotlib, Seaborn)

• Lead feature engineering efforts to improve model performance

• Perform statistical testing and hypothesis validation to support business decisions

• Design, build, and optimize custom machine learning algorithms

• Collaborate with IT and data engineering to access and integrate data from varied sources

• Deploy machine learning models in production for real-time applications

• Design and analyze A/B testing experiments

• Ensure compliance with data privacy and ethical standards

• Partner with business and technical teams to align data science efforts with organizational goals

• Mentor junior data scientists and promote a data-driven culture

• Define long-term strategy for data science initiatives and innovation

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Qualifications:

• Master’s or Ph.D. in a quantitative discipline

• 10–15 years of experience in data science, including leadership roles

• Strong programming skills in Python, R, or Julia

• Expert in advanced machine learning and statistical modeling

• Experienced in big data ecosystems (e.g., Hadoop, Spark)

• Proficient in SQL and data wrangling techniques

• Strong communication and storytelling abilities for technical and non-technical audiences

• Deep understanding of data governance, ethics, and compliance

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Preferred Tools & Technologies:

• Languages/Frameworks: Python, R, SQL, Spark

• Visualization Tools: Tableau, Power BI, Python (Matplotlib, Seaborn, Plotly)

• Big Data Technologies: Hadoop, Spark, Kafka

• Machine Learning Libraries: Scikit-learn, TensorFlow, PyTorch, XGBoost