Data Scientist 2 - 4P/114

4P Consulting Inc.; Atlanta (GA); On-site; USD 90,000 - 130,000; Full time

Job summary

A leading company is seeking a Data Scientist with 5-10 years of experience to leverage data for actionable insights and predictive modeling. The ideal candidate should possess strong technical skills in programming and analytics, alongside the ability to mentor others and maintain ethical data practices. This role plays a critical part in decision-making processes and requires collaboration across teams to integrate and analyze diverse datasets effectively.

Qualifications

• 5-10 years of experience in data science, machine learning, and statistical analysis.
• Proficiency in Python, SQL, and data visualization tools.
• Strong problem-solving and communication skills.

Responsibilities

• Collect, clean, and analyze complex datasets for actionable insights.
• Develop and deploy machine learning models to forecast trends.
• Mentor junior data scientists and analysts.

Skills

Data Analysis

Machine Learning

Statistical Analysis

Problem Solving

Data Visualization

Communication

Education

Bachelor’s degree in a quantitative field

Master’s or Ph.D.

Tools

Python

R

SQL

Tableau

Power BI

Hadoop

Spark

Job description

Position: Data Scientist (5 to 10 Years of Experience)

US Citizen/ Greencard Preferred

Overview:
A Data Scientist with 5 to 10 years of experience plays a pivotal role in leveraging data to uncover actionable insights, create predictive models, and drive informed decision-making within an organization. This role requires expertise in advanced analytics, machine learning, and problem-solving to extract meaningful value from large and complex datasets.

Key Responsibilities:

1. Data Analysis

   • Collect, clean, and analyze complex datasets to identify trends, patterns, and actionable insights.
   • Apply statistical techniques to derive meaningful information from data.

2. Predictive Modeling

   • Develop and deploy machine learning models to forecast trends, behaviors, and outcomes.
   • Employ techniques such as regression analysis, clustering, and classification.

3. Data Visualization

   • Design and present compelling visualizations to communicate findings effectively to technical and non-technical audiences using tools like Tableau, Power BI, or Python libraries.

4. Hypothesis Testing

   • Formulate and validate hypotheses to support data-driven business decisions.

5. Feature Engineering

   • Engineer and optimize features to enhance the performance of machine learning models.

6. Algorithm Development

   • Build, test, and fine-tune algorithms, including decision trees, random forests, neural networks, and more, tailored to specific challenges.

7. Data Integration

   • Collaborate with IT teams to integrate and access data from diverse sources and data warehouses.

8. Model Deployment

   • Implement machine learning models in production to support real-time decision-making.

9. A/B Testing

   • Design and analyze A/B tests to evaluate the impact of interventions and enhancements.

10. Data Ethics

    • Ensure adherence to ethical data practices, including privacy standards and compliance with data protection regulations.

11. Cross-functional Collaboration

    • Partner with engineers, business analysts, and domain experts to align data initiatives with organizational goals.

12. Mentorship

    • Mentor and guide junior data scientists and analysts to foster their professional development.

13. Continuous Learning

    • Stay abreast of the latest tools, techniques, and trends in data science through ongoing education and professional development.

Qualifications:

• Education:

  • Bachelor’s degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering). A Master’s or Ph.D. is preferred.

• Experience:

  • 5 to 10 years of hands-on experience in data science, including machine learning and statistical analysis.

• Technical Skills:

  • Proficiency in programming languages such as Python, R, or Julia.
  • Solid understanding of machine learning algorithms and their practical applications.
  • Expertise in data visualization tools (e.g., Tableau, Power BI) or Python libraries (e.g., Matplotlib, Seaborn).
  • Strong skills in SQL for data manipulation and querying.
  • Familiarity with big data technologies (e.g., Hadoop, Spark) is an advantage.

• Soft Skills:

  • Excellent problem-solving and critical-thinking abilities.
  • Strong communication skills to convey complex insights effectively to varied audiences.

• Ethics and Compliance:

  • Knowledge of data privacy, ethical considerations, and compliance frameworks.

Summary:
A seasoned Data Scientist with 5 to 10 years of experience is an invaluable contributor to any organization. This professional combines technical expertise, advanced analytics, and strategic thinking to transform data into actionable insights, optimize decision-making, and mentor emerging talent, ensuring sustainable growth in data-driven operations.