Energy Jobline ZR
Job Description
4P Consulting Inc. is seeking a highly skilled
Data Scientist
to join our team. As a Data Scientist, you will leverage your expertise in data analysis and machine learning to extract valuable insights, solve complex problems, and support data‑driven decisions. You will work with large datasets to drive innovation and help organizations improve performance across a variety of industries, including finance, healthcare, and technology.
Key Responsibilities
Data Collection: Gather and collect large datasets from multiple sources, including APIs, databases, and external providers.
Data Cleaning: Preprocess and clean data to ensure consistency, address missing values, and remove outliers.
Exploratory Data Analysis (EDA): Conduct in‑depth analysis to understand data characteristics and patterns.
Feature Engineering: Develop features from raw data to enhance machine learning models.
Machine Learning Modeling: Implement and develop machine learning models for business problems, including classification, regression, clustering, and recommendations.
Model Evaluation: Assess and fine‑tune models using relevant evaluation metrics for optimal performance.
Data Visualization: Create clear, insightful visualizations and reports to present findings to non‑technical stakeholders.
Predictive Analytics: Utilize statistical and machine learning techniques to predict trends and future outcomes.
Statistical Analysis: Apply statistical methods to test hypotheses and analyze data.
A/B Testing: Design and execute A/B tests to evaluate changes and improvements.
Data Integration: Integrate data science solutions into existing workflows and software systems.
Data Security: Ensure data privacy by implementing appropriate security measures.
Documentation: Maintain clear documentation of processes, models, and findings.
Continuous Learning: Stay current on developments in data science and machine learning.
Qualifications
Education: Bachelor's degree in Computer Science, Statistics, Mathematics, or related field (Master's or Ph.D. optional).
Programming Skills: Proficiency in Python or R.
Data Tools: Experience with machine learning and data analysis libraries (e.g., Pandas, NumPy, Scikit‑Learn, TensorFlow, PyTorch).
Database Knowledge: Strong understanding of SQL and relational databases.
Statistical Skills: Expertise in statistical analysis techniques.
Machine Learning: Deep knowledge of machine learning algorithms and techniques.
Data Visualization: Proficient in tools like Matplotlib, Seaborn, or Tableau.
Problem‑Solving: Strong analytical and problem‑solving skills.
Communication: Ability to clearly explain complex findings to non‑technical audiences.
Collaboration: Experience working within cross‑functional teams.
Domain Knowledge: Relevant industry experience (e.g., healthcare, finance) may be required.
Ethical Considerations: Knowledge of ethical data analysis practices, including privacy and bias concerns.
Benefits
Competitive salary
Opportunities for career growth and development
Health and wellness benefits
Collaborative and dynamic work environment
How to Apply Please submit your resume and a cover letter to info@4pconsultinginc.com detailing your experience and why you’d be a great fit for the Data Scientist role.
If you are interested in applying for this job, please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.
#J-18808-Ljbffr
Data Scientist
to join our team. As a Data Scientist, you will leverage your expertise in data analysis and machine learning to extract valuable insights, solve complex problems, and support data‑driven decisions. You will work with large datasets to drive innovation and help organizations improve performance across a variety of industries, including finance, healthcare, and technology.
Key Responsibilities
Data Collection: Gather and collect large datasets from multiple sources, including APIs, databases, and external providers.
Data Cleaning: Preprocess and clean data to ensure consistency, address missing values, and remove outliers.
Exploratory Data Analysis (EDA): Conduct in‑depth analysis to understand data characteristics and patterns.
Feature Engineering: Develop features from raw data to enhance machine learning models.
Machine Learning Modeling: Implement and develop machine learning models for business problems, including classification, regression, clustering, and recommendations.
Model Evaluation: Assess and fine‑tune models using relevant evaluation metrics for optimal performance.
Data Visualization: Create clear, insightful visualizations and reports to present findings to non‑technical stakeholders.
Predictive Analytics: Utilize statistical and machine learning techniques to predict trends and future outcomes.
Statistical Analysis: Apply statistical methods to test hypotheses and analyze data.
A/B Testing: Design and execute A/B tests to evaluate changes and improvements.
Data Integration: Integrate data science solutions into existing workflows and software systems.
Data Security: Ensure data privacy by implementing appropriate security measures.
Documentation: Maintain clear documentation of processes, models, and findings.
Continuous Learning: Stay current on developments in data science and machine learning.
Qualifications
Education: Bachelor's degree in Computer Science, Statistics, Mathematics, or related field (Master's or Ph.D. optional).
Programming Skills: Proficiency in Python or R.
Data Tools: Experience with machine learning and data analysis libraries (e.g., Pandas, NumPy, Scikit‑Learn, TensorFlow, PyTorch).
Database Knowledge: Strong understanding of SQL and relational databases.
Statistical Skills: Expertise in statistical analysis techniques.
Machine Learning: Deep knowledge of machine learning algorithms and techniques.
Data Visualization: Proficient in tools like Matplotlib, Seaborn, or Tableau.
Problem‑Solving: Strong analytical and problem‑solving skills.
Communication: Ability to clearly explain complex findings to non‑technical audiences.
Collaboration: Experience working within cross‑functional teams.
Domain Knowledge: Relevant industry experience (e.g., healthcare, finance) may be required.
Ethical Considerations: Knowledge of ethical data analysis practices, including privacy and bias concerns.
Benefits
Competitive salary
Opportunities for career growth and development
Health and wellness benefits
Collaborative and dynamic work environment
How to Apply Please submit your resume and a cover letter to info@4pconsultinginc.com detailing your experience and why you’d be a great fit for the Data Scientist role.
If you are interested in applying for this job, please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.
#J-18808-Ljbffr