We are seeking a highly motivated and versatile Data Scientist who not only excels in data modeling and analytics but also brings strong foundational skills in scripting, databases, networking, Linux systems, and version control. The ideal candidate will be passionate about leveraging data to drive business decisions while operating effectively in a multi-disciplinary technical environment.
Key Responsibilities:
- Analyze large datasets to extract actionable insights and present findings to stakeholders.
- Design and automate data pipelines and data processing workflows and work with developers to integrate new data pipelines.
- Participate in data integration projects with a client and product team and come up with solutions when a dataset does not fit the current model.
- Collaborate with IT/network teams to access, manage, and secure data sources across different networked environments.
- Perform SQL database querying, maintenance, and optimization (Microsoft SQL Server or similar).
- Operate comfortably within Linux environments for data processing, scripting, and deployment tasks.
- Test and deploy software using bash or python scripts.
- Use Git and version control practices for code management, collaboration, and project documentation.
Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Information Systems, or a related technical field.
- 3+ years of hands-on experience in data science, machine learning, or applied analytics roles.
- Proficiency in Python additional scripting languages (e.g., Bash, PowerShell) are a plus.
- SQL skills, preferably on Microsoft SQL Server, with ability to write queries for analyzation of data.
- Familiarity with networking concepts (basic TCP/IP, DNS, VPNs, etc.) and ability to troubleshoot data access across networks.
- Practical experience working in Linux environments (command-line proficiency, cron jobs, basic system administration tasks).
- Experience using Git for version control, code reviews, and team collaboration.
- Ability to work independently as well as collaboratively across cross-functional teams.
Preferred Qualifications:
- Experience deploying data science solutions into production environments.
- Knowledge of cloud platforms (Azure, AWS, or GCP) is a strong plus.
- Understanding of container technologies like Docker is an advantage.
- Familiarity with data visualization tools (Power BI, Tableau, or open-source equivalents).
- Knowledge of basic DevOps or CI/CD practices related to data science projects.
Personal Skills:
- Strong analytical, problem-solving, and critical-thinking skills.
- Excellent communication skills – able to explain complex data topics to non-technical stakeholders.
- Highly organized and detail-oriented with a proactive approach to troubleshooting and learning.
