Data Scientist

Data Scientist

Location: Atlanta, GA (Hybrid)

A Data Scientist with 5 to 10 years of experience is responsible for leveraging data to uncover insights, create predictive models, and drive data-driven decision-making within an organization. This role involves advanced analytics, machine learning, and strong problem-solving skills to extract actionable information from large datasets.

Key Responsibilities

Data Analysis: Collect, clean, and analyze complex datasets to identify trends, patterns, and actionable insights. Use statistical techniques to uncover meaningful information from data.

Predictive Modeling: Develop and deploy machine learning models to predict future trends, behaviors, and outcomes. Apply regression analysis, clustering, classification, and other modeling techniques.

Data Visualization: Create compelling data visualizations to communicate findings effectively to both technical and non-technical stakeholders using tools like Tableau, Power BI, or Python libraries.

Hypothesis Testing: Formulate and test hypotheses, providing statistical validation for business decisions and recommendations.

Feature Engineering: Engineer and select relevant features for machine learning models, enhancing their predictive power.

Algorithm Development: Build and fine-tune machine learning algorithms, such as decision trees, random forests, neural networks, and more, depending on the specific problem.

Data Integration: Collaborate with IT and database administrators to integrate and access data from various sources and data warehouses.

Model Deployment: Deploy machine learning models in production environments to support real-time decision-making.

A/B Testing: Design and analyze A/B tests to measure the impact of changes and improvements.

Data Ethics: Ensure ethical data practices, including privacy and compliance with data protection regulations.

Cross-functional Collaboration: Collaborate with cross-functional teams, including engineers, business analysts, and domain experts, to understand business requirements and align data science initiatives with organizational goals.

Mentorship: Provide guidance and mentorship to junior data scientists and analysts, fostering their professional growth.

Continuous Learning: Stay updated on the latest data science tools, techniques, and trends through ongoing professional development.

Qualifications
• Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering); a Master's or Ph.D. is a plus.
• 5 to 10 years of experience in data science, including machine learning and statistical analysis.
• Proficiency in data analysis tools and programming languages such as Python, R, or Julia.
• Strong knowledge of machine learning algorithms and their applications. Experience with data visualization tools like Tableau, Power BI, or data visualization libraries in Python (e.g., Matplotlib, Seaborn).
• Solid understanding of databases and data manipulation using SQL.
• Excellent problem-solving and critical thinking skills.
• Strong communication skills to convey complex findings and insights to both technical and non-technical stakeholders.
• Familiarity with big data technologies and distributed computing frameworks is a plus (e.g., Hadoop, Spark).
• Knowledge of data ethics, privacy, and compliance considerations.
• A Data Scientist with 5 to 10 years of experience is a critical asset to an organization, capable of transforming data into actionable insights, building predictive models, and driving data driven decision-making.
• This role requires a strong foundation in data science techniques, programming, and advanced analytics, as well as the ability to collaborate with various teams and mentor junior staff.