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Manager Data Analyst Machine Learning Jobs in Alaska

WFN Team Indus US Test Client 2

Data Analyst

Anchorage, AK · On-site

$1.5K - $2.0K/yr

Familiarity with advanced data analysis techniques and machine learning algorithms. * Knowledge of database management systems and SQL. Responsibilities: * Collect, clean, and preprocess agricultural ...

WFN Team Indus US Test Client 2

Data Analyst

Anchorage, AK · On-site

$12.10/hr

We are a global leader in human resources technology, offering the latest AI and machine learning ... Excellent project management skills * Strong verbal and interpersonal skills, with demonstrated ...

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Manager Data Analyst Machine Learning information

What is the difference between Manager Data Analyst Machine Learning vs Data Scientist?

AspectManager Data Analyst Machine LearningData Scientist
Required CredentialsBachelor's/Master's in Data Science, Analytics, or related; experience in machine learningBachelor's/Master's/PhD in Data Science, Statistics, or related; strong programming skills
Work EnvironmentTeam leadership, project management, cross-department collaborationResearch, model development, data exploration
Employer & Industry UsageBusiness analytics, tech companies, finance, healthcareTech firms, research institutions, consulting

While both roles involve data analysis and machine learning, the Manager Data Analyst Machine Learning focuses on leading teams and managing projects, whereas Data Scientists primarily develop models and perform in-depth data research.

What cities in Alaska are hiring for Manager Data Analyst Machine Learning jobs? Cities in Alaska with the most Manager Data Analyst Machine Learning job openings:
Manager Data Analyst Machine Learning jobs near you

Data Analyst

WFN Team Indus US Test Client 2

Anchorage, AK • On-site

$1.5K - $2.0K/yr

Full-time

Posted 7 days ago

Job description

About the Role:

The Data Analyst will play a crucial role in transforming raw agricultural data into actionable insights that drive decision-making and improve operational efficiency. This position involves analyzing complex datasets to identify trends, patterns, and anomalies that can inform strategic initiatives within the agriculture sector. The successful candidate will collaborate with cross-functional teams to ensure data integrity and accuracy, enabling the organization to leverage data for enhanced productivity and sustainability. Additionally, the Data Analyst will be responsible for creating compelling visualizations and reports that communicate findings to stakeholders at all levels. Ultimately, this role is essential for fostering a data-driven culture within the organization and supporting its mission to innovate in the agricultural industry.

Minimum Qualifications:

  • Bachelor's degree in Data Science, Statistics, Agriculture, or a related field.
  • Proven experience in data analysis and data visualization tools such as Power BI and Tableau.
  • Strong proficiency in R and SAS programming languages.

Preferred Qualifications:

  • Experience in the agriculture industry or related fields.
  • Familiarity with advanced data analysis techniques and machine learning algorithms.
  • Knowledge of database management systems and SQL.

Responsibilities:

  • Collect, clean, and preprocess agricultural data from various sources to ensure high-quality datasets.
  • Utilize statistical tools and programming languages such as R and SAS to perform data analysis and generate insights.
  • Create and maintain interactive dashboards and visualizations using Power BI and Tableau to present data findings to stakeholders.
  • Collaborate with agronomists and other team members to understand data requirements and provide analytical support for ongoing projects.
  • Conduct regular data audits and implement data cleansing processes to maintain data accuracy and reliability.

Skills:

The required skills in data cleaning and data extraction are essential for ensuring that the datasets used for analysis are accurate and reliable. Proficiency in pivot tables and data visualization tools like Power BI and Tableau allows the Data Analyst to create insightful reports that effectively communicate findings to stakeholders. The use of R and SAS programming languages is critical for performing complex statistical analyses and modeling. Daily work will involve collaborating with team members to understand their data needs, which requires strong communication and problem-solving skills. Preferred skills, such as familiarity with machine learning algorithms, can enhance the analyst's ability to derive deeper insights and contribute to innovative projects.

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