Data Science Engineer

Seeking a skilled Data Science Engineer to join our dynamic team! Utilize your expertise in machine learning, statistical analysis, and big data technologies to develop and implement innovative data solutions. Collaborate with cross-functional teams to drive business insights and optimize data processes. Apply now to make a significant impact.

Job TitleData Science Engineer
LocationRemote
DepartmentData Science
Reports ToHead of Data Science
Job SummaryThe Data Science Engineer will develop and implement machine learning models, algorithms, and computational analytics to solve complex business problems. This role requires strong programming skills, statistical analysis, and the ability to work with large datasets.
Key Responsibilities– Develop, construct, test, and maintain architectures such as databases and large-scale processing systems.<br>- Design and implement machine learning models and algorithms.<br>- Analyze and interpret complex data sets to provide actionable insights.<br>- Collaborate with data scientists, data engineers, and other stakeholders to understand data needs.<br>- Optimize data processes and ensure data quality and integrity.<br>- Create and maintain detailed documentation of data processes and models.<br>- Stay updated with the latest industry trends and technologies.
Qualifications– Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.<br>- 3+ years of experience in data science or related roles.<br>- Proficiency in programming languages such as Python, R, and SQL.<br>- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).<br>- Strong understanding of statistical analysis and data visualization tools.<br>- Experience with big data technologies (e.g., Hadoop, Spark) is a plus.
Skills– Advanced knowledge of data analytics, cleaning, and preparation.<br>- Proficiency with data modeling and analysis tools.<br>- Expertise in programming languages (Python, R, SQL).<br>- Experience with statistical and mathematical analysis.<br>- Critical thinking and problem-solving skills.<br>- Excellent verbal and written communication skills.<br>- Ability to work collaboratively in a team environment.
Tools and Technologies– Python, R, SQL<br>- Data visualization tools (e.g., Tableau, Power BI)<br>- Machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)<br>- Big data technologies (e.g., Hadoop, Spark)
Soft Skills– Strong analytical and critical thinking skills.<br>- Excellent communication and presentation skills.<br>- Ability to work collaboratively in a team environment.<br>- Leadership and mentorship abilities.
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