Location: Atlanta, GA
Experience: 6-10 years
Employment Type: Full-time
Position Overview
As a Senior Data Scientist, you will design, build, and deploy machine learning models with a focus on classification, regression, and clustering techniques. You’ll work on the entire lifecycle of model development from data preprocessing and exploratory data analysis to model building, evaluation, and deployment.
Key Responsibilities
- Lead end-to-end development of machine learning solutions from data collection and preprocessing to model deployment and monitoring
- Apply advanced statistical and predictive modeling techniques to address complex business problems
- Perform thorough exploratory data analysis to understand patterns, detect anomalies, and extract valuable insights
- Develop and optimize classification models (Logistic Regression, Decision Tree, Random Forest) for targeted business applications
- Create regression models (Linear, Gradient Boosting, Neural Networks, KNN) to predict continuous variables with high accuracy
- Implement unsupervised learning techniques (K-means and other clustering approaches) to segment data and identify natural groupings
- Collaborate with cross-functional teams to translate business requirements into data science problems
- Evaluate model performance using appropriate metrics and techniques, ensuring models meet business objectives
- Document methodologies, processes, and findings to ensure reproducibility and knowledge sharing
- Communicate complex technical concepts to both technical and non-technical stakeholders
- Requirements
- Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, or related field (Master’s or PhD preferred)
- 6-10 years of hands-on experience in data science with focus on predictive modeling
- Proven expertise in developing and implementing the following models:
- Classification: Logistic Regression, Decision Tree, Random Forest
- Regression: Linear Regression, Gradient Boosting, Neural Networks, KNN
- Unsupervised Learning: K-means and other clustering techniques
- Strong proficiency in Python and its data science libraries (NumPy, pandas, scikit-learn, TensorFlow/PyTorch)
- Experience with big data technologies (Hadoop, Spark) and SQL
- Strong understanding of statistical concepts and their application to real-world problems
- Proven track record of delivering data science projects from conception to deployment
- Excellent communication skills with ability to translate complex findings into actionable insights
- Experience with data visualization tools (Tableau, Power BI) and ability to create compelling visualizations
- Preferred Qualifications
- Experience in the [industry sector] industry
- Knowledge of cloud-based machine learning platforms (AWS SageMaker, Azure ML, Google AI Platform)
- Experience with model deployment and MLOps practices
- Familiarity with deep learning frameworks and techniques
- Contribution to open-source projects or research publications
Benefits
- Competitive salary and performance bonus
- Comprehensive health, dental, and vision insurance
- 401(k) with company match
- Flexible work arrangements
- Professional development and continuous learning opportunities
- Collaborative and innovative work environment
Our company is an Equal Opportunity Employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.
Application Process: Qualified candidates should submit their resume, cover letter, and a brief description of relevant data science projects they’ve led.
