DATA SCIENTIST

ZipRecruiter; Portland (OR); On-site; USD 95,000 - 130,000; Full time

Job summary

A leading company is seeking a Data Scientist with expertise in machine learning and data analysis. The role involves transforming data into actionable insights, building predictive models, and driving data-driven decision-making. Candidates should have strong programming skills and the ability to communicate complex findings effectively.

Qualifications

• 5 to 10 years of experience in data science, including machine learning.
• Strong knowledge of machine learning algorithms and their applications.

Responsibilities

• Collect, clean, and analyze complex datasets to identify trends.
• Develop and deploy machine learning models to predict future trends.

Skills

Data Analysis

Machine Learning

Statistical Analysis

Problem Solving

Communication

Education

Bachelor's degree in a quantitative field

Master's or Ph.D.

Tools

Python

R

SQL

Tableau

Power BI

Job description

Job Description

HI,

Hope you're doing well.

This is Pankaj from 4P Consulting. Please see below the job description.

Please share your resume if you're interested and have 5-10 years of experience. Submission on W2 basis only. NO C2C.

Responsibilities:

1. Data Analysis: Collect, clean, and analyze complex datasets to identify trends, patterns, and actionable insights. Use statistical techniques to uncover meaningful information from data.
2. Predictive Modeling: Develop and deploy machine learning models to predict future trends, behaviors, and outcomes. Apply regression analysis, clustering, classification, and other modeling techniques.
3. Data Visualization: Create compelling data visualizations to communicate findings effectively to both technical and non-technical stakeholders using tools like Tableau, Power BI, or Python libraries.
4. Hypothesis Testing: Formulate and test hypotheses, providing statistical validation for business decisions and recommendations.
5. Feature Engineering: Engineer and select relevant features for machine learning models to enhance their predictive power.
6. Algorithm Development: Build and fine-tune machine learning algorithms such as decision trees, random forests, neural networks, etc.
7. Data Integration: Collaborate with IT and database administrators to access data from various sources and data warehouses.
8. Model Deployment: Deploy machine learning models in production environments to support real-time decision-making.
9. A/B Testing: Design and analyze A/B tests to measure the impact of changes and improvements.
10. Data Ethics: Ensure ethical data practices, including privacy and compliance with data protection regulations.
11. Cross-Functional Collaboration: Work with engineers, business analysts, and domain experts to align data science initiatives with organizational goals.
12. Mentorship: Provide guidance and mentorship to junior data scientists and analysts.
13. Continuous Learning: Stay updated on the latest tools, techniques, and trends in data science.

Qualifications:

• Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering); a Master's or Ph.D. is a plus.
• 5 to 10 years of experience in data science, including machine learning and statistical analysis.
• Proficiency in data analysis tools and programming such as Python, R, or Julia.
• Strong knowledge of machine learning algorithms and their applications.
• Experience with data visualization tools like Tableau, Power BI, or visualization libraries in Python (e.g., Matplotlib, Seaborn).
• Solid understanding of databases and data manipulation using SQL.
• Excellent problem-solving and critical thinking skills.
• Strong communication skills to convey complex findings to technical and non-technical stakeholders.
• Familiarity with big data technologies and distributed computing frameworks (e.g., Hadoop, Spark) is a plus.
• Knowledge of data ethics, privacy, and compliance considerations.

This role is critical for transforming data into actionable insights, building predictive models, and driving data-driven decision-making. It requires a strong foundation in data science techniques, programming, and analytics, along with collaboration and mentorship skills.

Thanks and Regards,

Sr. Talent Acquisition Specialist

Pankaj Mishra

[e-mail]

[phone]