Roles & Skills
ECLARO delivers top talent for a variety of Data Scientist roles, tailored to meet different project needs, skills, and levels of experience and expertise. Although the specifics and titles may vary for each individual business, our experienced recruiters have a track record of success in helping businesses hire at all levels
Junior Data Scientists
Focus on gathering and cleaning data, developing basic predictive models, and assisting in data analysis tasks.
Mid-Level Data Scientists
Handle more complex data analysis and modeling tasks, integrate data from various sources, and contribute to the development of new data-driven insights and strategies.
Senior Data Scientists
Lead data strategy and analysis, develop and implement advanced data models, and manage data science projects from start to finish.
Key skills
- Python and statistical programming (R, SQL, pandas)
- Machine learning model development and evaluation
- Data analysis, visualization, and storytelling with data
- Big data tools and cloud platforms (AWS, GCP, Azure)
- Business acumen and translating technical insights to stakeholders
- A/B testing and experimental design
- Communication and cross-functional collaboration
Frequently asked questions
What does a Data Scientist do day-to-day?
Data Scientists spend their time exploring data to identify patterns, building and training machine learning models to solve business problems, and communicating findings to non-technical stakeholders. A typical day might include writing Python code to process datasets, running experiments to test hypotheses, creating data visualizations, collaborating with engineers on model deployment, and presenting recommendations to leadership. They bridge analytics and engineering, turning raw data into actionable insights.
What qualifications and certifications should I look for?
Most Data Scientists hold a degree in mathematics, statistics, computer science, physics, or economics. Advanced degrees (Master's or PhD) in these fields are common but not always required——many come from bootcamps or self-taught backgrounds with strong portfolios. Valuable certifications include AWS Certified Machine Learning Specialty, Google Cloud Professional Data Engineer, or Coursera credentials in machine learning and data science. More importantly, look for candidates with demonstrable experience shipping models to production and a portfolio of projects showcasing their technical depth.
How does ECLARO help me find and hire a Data Scientist?
ECLARO sources vetted Data Scientists through a rigorous screening process that evaluates both technical skills and cultural fit. We handle recruitment, reference checks, and background verification, saving your team weeks of hiring effort. Whether you need a contract-to-hire specialist for a short-term analytics project or a full-time senior Data Scientist to lead your ML initiative, ECLARO matches you with candidates who have been validated for the specific tools, methodologies, and domain experience your team requires. We also provide ongoing support throughout the placement to ensure success.
What's the difference between a Data Scientist and a Data Analyst?
Data Analysts focus on descriptive and diagnostic analytics—answering "what happened" and "why did it happen" through dashboards and SQL queries. Data Scientists take a broader approach, building predictive and prescriptive models using machine learning, designing experiments, and tackling complex strategic problems. Data Scientists typically have stronger programming skills and statistical foundations. Both roles are critical; some teams hire both, while others need specialists who bridge both skill sets. ECLARO can help you determine which roles best fit your organizational needs.
Ways to hire through ECLARO
ECLARO can fill this role through contract or contract-to-hire staffing, direct placement, an Employer of Record (EOR), recruitment process outsourcing (RPO), or a dedicated offshore team in the Philippines (ECAPTIVE).