Junior Data Scientist with Data Engineering Skills

Overview Seeking a motivated Junior Data Scientist with Data Engineering skills to join our analytics and engineering teams. This is an opportunity for recent graduates or early-career professionals who are passionate about data, machine learning, and building scalable data pipelines. You will work on projects that combine data science, data engineering, and DevOps practices to deliver actionable insights and enterprise-grade solutions for U.S.-based clients. Responsibilities Collect, clean, and preprocess large datasets for analysis and modeling Build and maintain ETL pipelines and scalable data workflows Develop predictive models and machine learning algorithms Collaborate with DevOps teams to deploy models into production environments Work with cross-functional teams to translate business requirements into technical solutions Optimize data storage and retrieval using SQL/NoSQL databases and cloud platforms Required Qualifications Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent experience) Strong knowledge of Python, SQL, and data manipulation libraries (Pandas, NumPy, Scikit-learn) Familiarity with data engineering tools such as Spark, Hadoop, or Kafka Exposure to cloud platforms (AWS, Azure, or GCP) Understanding of DevOps practices for model deployment Excellent problem-solving and communication skills Additional Skills Experience with deep learning frameworks (TensorFlow, PyTorch) Knowledge of data visualization tools (Tableau, Power BI, Matplotlib, Seaborn) Internship or project experience in data science or data engineering Client Requirements Real-world project experience: Hands-on exposure to enterprise-level data science and engineering projects beyond academic coursework U.S. work experience: Familiarity with U.S. client expectations, delivery standards, and collaborative team environments #J-18808-Ljbffr SynergisticIT