Data Scientist

Job Title: Data Scientist

Location: Johns Creek (Hybrid)

Duration: 12+ Months

Job Description:

We are seeking a highly analytical and motivated Data Scientist to join our team. The ideal candidate will leverage statistical analysis, machine learning, and data mining techniques to derive actionable insights from complex datasets. The candidate will work closely with business stakeholders, data engineers, and product teams to develop predictive models, optimize business processes, and support data-driven decision-making.

Required Skills & Qualifications

• Bachelor//'s or Master//'s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• Strong proficiency in Python and/or R.
• Experience with SQL and database technologies.
• Hands-on experience with machine learning libraries such as Scikit-Learn, TensorFlow, PyTorch, or XGBoost.
• Strong understanding of statistics, probability, and predictive modeling.
• Experience with data visualization tools such as Tableau, Power BI, or Matplotlib.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Experience with big data technologies such as Spark, Hadoop, or Databricks is a plus.
• Excellent problem-solving, communication, and stakeholder management skills.

Preferred Qualifications

• Experience in healthcare, life sciences, finance, retail, or relevant industry domains.
• Knowledge of Generative AI, LLMs, NLP, and MLOps frameworks.
• Experience deploying machine learning models in production environments.
• Familiarity with Git, CI/CD pipelines, Docker, and Kubernetes.

Key Responsibilities

• Analyze large, complex datasets to identify trends, patterns, and business opportunities.
• Develop, validate, and deploy machine learning and statistical models.
• Design and implement predictive and prescriptive analytics solutions.
• Perform data cleaning, feature engineering, and exploratory data analysis (EDA).
• Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions.
• Create dashboards, visualizations, and reports to communicate findings effectively.
• Monitor model performance and continuously improve model accuracy and efficiency.
• Conduct A/B testing and hypothesis testing to support business initiatives.
• Work with structured and unstructured data from multiple sources.
• Stay updated on emerging data science, AI, and machine learning technologies and best practices.