Data Scientist
Listed on 2025-12-22
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IT/Tech
Data Scientist, Machine Learning/ ML Engineer, Data Analyst, AI Engineer
Job Title: Senior Data Scientist
Experience: 10–15 Years
Location:Atlanta, Ga
Contract- 1 Year
Client Southern Company
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.
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
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
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, Tensor Flow, PyTorch, XGBoost
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