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Diverse Lynx

Data Analyst Specialist

Diverse Lynx, New York, New York, us, 10261


Job Title Data Analyst Specialist

Location : New York, NY (On-site)

Type Full time/ Permanent

Skills

Must Have Skills

Time series forecasting & predictive analytics techniques.Strong proficiency in data visualization platforms such as Tableau ,Qlikview and Looker.Experience in the Media, Adtech, or Entertainment industry domains is highly desirableStrong programming skills in Python or R for data analysis and model implementation.Proficiency in SQL for data extraction and manipulation.

Roles & Responsibilities

Time Series Analysis:

Analyze historical time series data to identify patterns, trends, and seasonality using statistical methods.Apply various time series techniques, such as moving averages, exponential smoothing, and decomposition, to forecast future performance metrics.Determine appropriate model selection and parameter tuning based on data characteristics and forecast requirements.

Predictive Analytics:

Utilize predictive modeling techniques to build and evaluate models that forecast future outcomes and performance.Apply machine learning algorithms, such as regression, decision trees, and ensemble methods, to develop predictive models.Assess model accuracy and performance through cross-validation and other evaluation metrics.

Data Visualization:

Develop visually compelling and interactive dashboards and reports to present key insights and forecasts to stakeholders.Use data visualization platforms such as Tableau and Looker to create intuitive charts, graphs, and visualizations for data storytelling.Collaborate with cross-functional teams to understand their data visualization needs and deliver actionable insights through compelling visualizations.

Data

Analysis and Interpretation:

Analyze large datasets to identify trends, anomalies, and opportunities for business improvement.Interpret and communicate findings to stakeholders in a clear and concise manner, highlighting relevant implications for the organization.Provide data-driven recommendations and actionable insights to support strategic planning and operational decision-making.

Data Quality Assurance:

Ensure data accuracy, integrity, and consistency across various data sources used for time series analysis and predictive modeling.Identify and rectify data quality issues, working closely with data engineering teams when necessary.

Continuous Learning and Innovation:

Stay updated with the latest advancements in time series analysis and predictive analytics techniques, as well as industry best practices.Propose and implement innovative solutions to enhance data analysis and predictive modeling processes.

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