Data Scientist (Entry Level)

• Collect, clean, and preprocess large datasets using ETL (Extract, Transform, Load) techniques to ensure data quality and readiness for analysis.
• Develop and train machine learning models utilizing frameworks such as TensorFlow, Spark MLlib, and other AI/ML platforms to perform predictive modeling analysis.
• Conduct statistical analysis for research purposes, applying tools like R, SAS, or Python to uncover patterns and insights from complex data sources.
• Implement unsupervised learning algorithms for clustering, anomaly detection, and natural language processing tasks to derive actionable intelligence.
• Design and optimize SQL databases and big data systems like Hadoop or Spark for efficient data storage and retrieval.
• Collaborate on model evaluation and deployment processes within cloud environments such as AWS or machine learning cloud services to ensure scalability and robustness.
• Support data mining initiatives using tools like Talend or Looker to visualize trends and communicate findings effectively across teams.
• Assist in the development of AI models that incorporate linked data, generative AI techniques, and natural language processing for innovative applications.
• Contribute to the continuous improvement of analytics workflows by integrating statistical modeling tools and machine learning frameworks into existing systems., Join us in shaping the future of analytics by harnessing the power of big data systems, AI models, and innovative machine learning techniques!

We are seeking a motivated and detail-oriented Entry-Level Data Scientist to join our innovative analytics team. In this role, you will leverage your passion for data and machine learning to extract meaningful insights, develop predictive models, and support AI-driven decision-making processes. This position offers an exciting opportunity to work with cutting-edge big data systems, cloud services, and advanced statistical tools to solve real-world problems. You will collaborate with cross-functional teams to implement scalable AI solutions that enhance business strategies and operational efficiency., * Bachelor's degree in Data Science, Computer Science, Statistics, or a related field; recent graduates are encouraged to apply.

• Familiarity with programming languages such as Python, R, Java, or C for data analysis and model development.
• Basic understanding of big data technologies including Hadoop, Spark implementation, and SQL databases.
• Exposure to machine learning concepts like predictive modeling analysis, model training/evaluation, and AI implementation strategies.
• Knowledge of cloud services such as AWS or other machine learning cloud platforms is a plus.
• Experience with statistical analysis tools like SAS or similar software is desirable but not mandatory.
• Strong analytical skills with an ability to interpret complex datasets and translate findings into actionable insights.
• Excellent communication skills to effectively present technical results to non-technical stakeholders.

• 401(k)