What Jobs are available for Data Analytics in Miami?

• Assist in collecting, cleaning, and preparing data for analysis.
• Perform data exploration and identify trends, patterns, and insights.
• Develop and maintain reports and dashboards using data visualization tools.
• Support senior analysts in conducting statistical analysis and building predictive models.
• Collaborate with cross-functional teams to understand data requirements and deliver insights.
• Document data processes and analytical methodologies.
• Present findings and recommendations to stakeholders in a clear and concise manner.
• Stay updated on emerging trends and best practices in data analytics.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a related quantitative field.
• Strong understanding of statistical concepts and data analysis techniques.
• Proficiency in data analysis tools and languages such as Python (Pandas, NumPy), R, SQL.
• Experience with data visualization tools (e.g., Tableau, Power BI) is a plus.
• Excellent analytical and problem-solving skills.
• Strong written and verbal communication skills, essential for remote collaboration.
• Ability to work independently and manage time effectively in a remote environment.
• A proactive attitude and a keen desire to learn and grow in the field of data analytics.

• Develop and implement advanced analytical models (e.g., regression, classification, clustering, time-series forecasting) to address business challenges in FMCG.
• Design and execute A/B tests and other experiments to measure the impact of marketing initiatives and product changes.
• Analyze large datasets from various sources (sales, marketing, consumer behavior, supply chain) to identify trends and opportunities.
• Build predictive models for demand forecasting, customer segmentation, churn prediction, and campaign effectiveness.
• Collaborate with stakeholders to define key performance indicators (KPIs) and design dashboards for monitoring business performance.
• Present complex analytical findings and recommendations to both technical and non-technical audiences in a clear and compelling manner.
• Stay current with the latest advancements in data science, machine learning, and AI.
• Mentor junior data scientists and contribute to the team's technical growth.

• Master's or Ph.D. in Statistics, Data Science, Computer Science, Economics, or a related quantitative field.
• Minimum of 5 years of experience in data science or advanced analytics, with a strong focus on the FMCG industry.
• Proficiency in Python or R, including relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas).
• Extensive experience with SQL and working with large datasets in data warehousing environments.
• Demonstrated experience with machine learning algorithms and statistical modeling techniques.
• Experience with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark).
• Excellent problem-solving, analytical, and communication skills.
• Ability to work effectively in a remote, collaborative team environment.

• Assist in data collection, cleaning, and preprocessing from various sources.
• Develop and implement machine learning models for predictive analytics.
• Perform feature engineering and selection to optimize model performance.
• Conduct exploratory data analysis to identify trends and insights.
• Validate and test model accuracy and robustness.
• Interpret model results and communicate findings to technical and non-technical stakeholders.
• Collaborate with senior data scientists on model deployment and monitoring.
• Stay up-to-date with the latest advancements in data science and machine learning techniques.
• Contribute to documentation and knowledge sharing within the data science team.

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• Strong foundational knowledge of statistical concepts and machine learning algorithms.
• Proficiency in Python or R for data analysis and modeling.
• Experience with SQL for database querying.
• Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Excellent analytical and problem-solving skills.
• Strong communication and teamwork abilities.
• Eagerness to learn and adapt in a dynamic field.
• Previous internship or project experience in data science is a plus.

• Clean, transform, and prepare marketing and customer data for analysis.
• Conduct exploratory data analysis to identify trends and patterns.
• Develop and implement statistical and machine learning models for marketing insights.
• Analyze campaign performance and provide recommendations for optimization.
• Build dashboards and reports to visualize key marketing metrics.
• Collaborate with marketing teams to understand data needs and deliver insights.
• Assist in A/B testing design and analysis.
• Contribute to the development of customer segmentation strategies.
• Stay up-to-date with emerging trends in data science and marketing analytics.
• Communicate findings and recommendations effectively to stakeholders.

• Bachelor's or Master's degree in Data Science, Statistics, Economics, Marketing Analytics, or a related quantitative field.
• Proficiency in Python or R for data analysis and modeling.
• Strong SQL skills for data querying and manipulation.
• Understanding of statistical concepts and machine learning algorithms.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong written and verbal communication skills.
• Ability to work effectively in a team environment.
• Internship or project experience in data science or marketing analytics preferred.

• Develop and deploy advanced statistical and machine learning models to address key business challenges in underwriting, claims, pricing, and fraud detection.
• Analyze large, complex datasets from various sources to extract actionable insights and identify trends.
• Design and conduct A/B tests and experiments to evaluate the effectiveness of new models and strategies.
• Build predictive models for risk assessment, customer lifetime value, churn prediction, and personalized product offerings.
• Collaborate with product managers, actuaries, and business leaders to define analytical requirements and translate business needs into data science solutions.
• Develop and maintain data pipelines, ensuring data quality and integrity for model development and deployment.
• Present complex analytical findings and recommendations to both technical and non-technical audiences clearly and concisely.
• Stay current with the latest advancements in data science, machine learning, and AI technologies.
• Mentor junior data scientists and contribute to the growth of the data science practice.
• Develop dashboards and visualizations to monitor key performance indicators and model performance.
• Ensure compliance with data privacy regulations and ethical AI practices.

• Master's or Ph.D. in Statistics, Data Science, Computer Science, Mathematics, Economics, or a related quantitative field.
• Minimum of 7 years of professional experience in data science, with a significant focus on developing and deploying machine learning models.
• Proven experience in the insurance industry or with insurance-related data.
• Expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and experimental design.
• Proficiency in programming languages such as Python or R, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas).
• Strong SQL skills for data extraction and manipulation.
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP) is highly desirable.
• Excellent communication, presentation, and interpersonal skills.
• Ability to work independently and collaboratively in a remote team environment.
• Strong business acumen and the ability to connect data insights to business impact.

Job Title: Data Analyst

Department: Education Management

Reporting Structure: Reports to the Director of Data Analytics

Summary:

Join our dynamic team at Atlantis University as a Data Analyst! We are seeking a detail-oriented individual who is passionate about transforming data into actionable insights. In this role, you will play a key part in driving data-driven decision making within the organization.

Responsibilities:

• Collect, clean, and analyze data from various sources


• Develop and maintain dashboards and reports to track key performance indicators


• Identify trends and patterns in data to provide insights for decision making


• Collaborate with cross-functional teams to support data-driven initiatives


• Conduct ad-hoc analysis to answer business questions

Qualifications:

• Bachelor's degree in a quantitative field such as Statistics, Mathematics, Economics, or Computer Science


• Proven experience working with data analysis tools such as SQL, Python, or R


• Strong analytical and problem-solving skills


• Excellent communication and presentation abilities


• Ability to work independently and as part of a team

Experience:

• 2+ years of experience in a data analysis role


• Experience in the Education Management industry is a plus


• Experience with data visualization tools such as Tableau or Power BI

If you are looking for an exciting opportunity to make a real impact with your data analysis skills, then we want to hear from you! Apply now to join the Atlantis University team.

• Assist in gathering data from various sources, ensuring data integrity and accuracy.
• Perform data cleaning and preprocessing tasks to prepare data for analysis.
• Support senior analysts in conducting quantitative analysis and generating reports.
• Develop basic visualizations and dashboards to communicate findings effectively.
• Identify trends, patterns, and anomalies in datasets.
• Contribute to the documentation of data processes and analytical methodologies.
• Collaborate with cross-functional teams to understand their data needs and provide analytical support.
• Participate in team meetings and contribute to ongoing projects.
• Learn and apply various data analysis tools and techniques.
• Assist in testing and validating analytical models and reports.

• Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or a related quantitative field.
• Strong understanding of statistical concepts and data analysis principles.
• Proficiency in Microsoft Excel, including formulas, pivot tables, and data manipulation.
• Familiarity with at least one data visualization tool (e.g., Tableau, Power BI) is a plus.
• Basic knowledge of SQL for data extraction is desirable.
• Excellent analytical and problem-solving skills.
• Strong attention to detail and accuracy.
• Good written and verbal communication skills.
• Ability to work effectively in a team environment and independently when required.
• Eagerness to learn and adapt to new technologies and methodologies.