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Entry Level Python Data Science Jobs in Ann Arbor, MI

Bachelor's degree in Data Science, Mathematics, Statistics, Industrial Operations Engineering ... Proficient in SQL & Python * Experience with API creation (i.e. functional programming, automated ...

... Python and at least one strongly typed language (e.g., C++, Java, etc.) * 3 years of experience ... Master's degree in mathematics, statistics, computer science or a related field or equivalent ...

... Python and at least one strongly typed language (e.g., C++, Java, etc.) * 3 years of experience ... Master's degree in mathematics, statistics, computer science or a related field or equivalent ...

Collaborate with engineering, product, and data science teams to understand requirements ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

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Entry Level Python Data Science information

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How much do entry level python data science jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for entry level python data science in Ann Arbor, MI is $57.35, according to ZipRecruiter salary data. Most workers in this role earn between $47.26 and $65.14 per hour, depending on experience, location, and employer.

What are some common challenges faced by entry-level Python data scientists when starting out, and how can they be addressed?

Entry-level Python data scientists often encounter challenges such as managing large datasets, understanding the nuances of real-world data (like missing or inconsistent values), and effectively communicating technical findings to non-technical stakeholders. To address these challenges, it's helpful to develop strong data cleaning skills, practice using libraries like pandas and scikit-learn, and focus on improving data visualization and storytelling abilities. Additionally, seeking feedback from more experienced team members and participating in collaborative projects can accelerate learning and help overcome early hurdles.

What is an entry level Python data scientist?

An entry level Python data scientist is a professional who uses Python programming language to analyze, interpret, and visualize data, typically in the early stages of their data science career. They are responsible for collecting, cleaning, and preparing data, performing basic statistical analyses, and building simple machine learning models under supervision. These roles often require proficiency in Python libraries like pandas, NumPy, and scikit-learn, as well as good problem-solving skills. Entry level data scientists may work in industries such as finance, healthcare, marketing, or technology to help organizations make data-driven decisions.

What are the key skills and qualifications needed to thrive as an Entry Level Python Data Scientist, and why are they important?

To thrive as an Entry Level Python Data Scientist, you need a strong understanding of statistics, data analysis, and proficiency in Python programming, typically supported by a relevant degree or coursework. Familiarity with data science libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and basic SQL is commonly required. Analytical thinking, problem-solving, and effective communication help you interpret data and present findings clearly. These skills ensure you can extract meaningful insights from data, collaborate effectively, and contribute to data-driven decision-making.

What is the difference between Entry Level Python Data Science vs Entry Level Data Analyst?

AspectEntry Level Python Data ScienceEntry Level Data Analyst
Required SkillsPython, SQL, statistics, machine learning basicsExcel, SQL, data visualization, basic statistics
CertificationsPython programming, data science fundamentalsExcel certifications, basic data analysis courses
Work EnvironmentTech companies, startups, data-driven teamsBusiness departments, marketing, finance teams
Common UsageBuilding models, data cleaning, predictive analyticsReporting, data visualization, trend analysis

Entry Level Python Data Science roles focus on programming, machine learning, and predictive modeling, often requiring Python and statistical knowledge. Entry Level Data Analyst positions emphasize data reporting, visualization, and basic analysis using tools like Excel and SQL. Both roles are common in various industries, but Python Data Science roles typically involve more technical and coding skills, while Data Analyst roles focus on interpreting data for business insights.

What are popular job titles related to Entry Level Python Data Science jobs in Ann Arbor, MI? For Entry Level Python Data Science jobs in Ann Arbor, MI, the most frequently searched job titles are:
What job categories do people searching Entry Level Python Data Science jobs in Ann Arbor, MI look for? The top searched job categories for Entry Level Python Data Science jobs in Ann Arbor, MI are:
What cities near Ann Arbor, MI are hiring for Entry Level Python Data Science jobs? Cities near Ann Arbor, MI with the most Entry Level Python Data Science job openings:
Data Scientist - Modeling and Analytics

Data Scientist - Modeling and Analytics

AAA Life Insurance Company

Livonia, MI

Full-time

Re-posted 4 days ago


Job description

Overview

Why AAA Life

AAA Life is a respected and trusted American brand that has been focusing on Life Insurance and Annuity Products since 1969. At AAA Life we have over 1.8 million policies where we take pride in earning the trust of our policyholders who understand our promise to be there for them - and their families - when we're needed most. By joining the AAA Life team, you are joining a company that genuinely cares about helping each other, with a devotion to protect the lives of those around us. We embrace a diverse, equitable, inclusive culture where all associates can feel a sense of belonging and use their unique talents and perspective to influence, innovate, motivate, and thrive.

How You'll Work

Work Solution: Hybrid 

Responsibilities

What You'll Do

As a Data Scientist - Modeling and Analytics, you will be responsible for creating statistical models and performing analyses that drive sales and policy growth for the organization. You will partner with marketing team members, marketing managers, and other data analysts and scientists to identify business needs, gather data, build, and maintain effective models, and assess model performance over time. This role requires proficiency in SQL for data manipulation, Sagemaker or other AI/ML tools for model building, R or Python for data analysis, and a visualization tool such as PowerBI for quickly assessing model performance. 
  • Build, maintain, and automate models to predict purchase propensity, policy premium, policy lapse/retention, cross-selling, upselling, next best action, and other consumer behaviors using both internal data, census data, appended aggregated data, and macroeconomic data. Recommend marketing distribution strategies leveraging data and models.  
  • Conduct advanced exploratory data analysis. Perform model interpretability and explainability analysis.  
  • Leverage specific metrics for model performance evaluation (e.g., precision, recall, F1 score). Implement A/B testing and experimental design and quantitative benchmarks for model improvement 
  • Apply data privacy and compliance rules under regulations like GDPR, CCPA. Apply ethical AI principles. Apply model fairness and bias mitigation techniques. 
  • Conduct analyses to assess model performance and campaign performance, both against test datasets and actual results once deployed. 
  • Forecast campaign results based on models built and validate forecast against actuals. 
  • Work with marketing data architects and engineers to ensure data is clean, complete, correct, and suitable for modeling using AI/ML platforms. 
  • Develop and maintain data pipelines. Implement feature engineering techniques. Find, recommend, and purchase additional data to use in model building 
  • Proactively identify opportunities for model improvement and need for additional modeling projects. 
  • Maintain clear and organized documentation of data, methodologies, and results. 
  • Implement automation in existing processes to improve overall efficiency. 
  • Perform ad hoc analysis to support Marketing Distribution efforts 
  • Actively seek out innovation and optimization use cases and experiments that will result in organizational transformation and sales and profit improvements. 
Qualifications

Qualifications

Basic Required Qualifications:

  • Skilled in cross-functional collaboration, agile methodologies, project management and stakeholder communication. 
  • Advanced training or academic focus in non-parametric statistics, resampling methods, or Bayesian approaches for small sample inference 
  • Experience applying sequential testing or multi-armed bandit approaches to maximize insights from limited samples in marketing contexts 
  • Able to effectively communicate and translate complex, technical finding in a candid, clear, concise, and non-technical fashion to all audiences 
  • Maintain perspective between the big picture and the tactical details. Remains aligned with the organization's strategic plan. 
  • Stellar attention to detail, including maintaining accuracy and consistency across a suite of data science assets, keeping documentation up to date, and proactively identifying and addressing any quality concerns. 
  • Self-starter with the ability to identify priorities and focus on items with high business impact.
  • Ability to present complex analytical findings with persuasiveness and succinctness.

Preferred Qualifications:

  • Master's degree in Statistics, Economics, Mathematics, Data Science, or related field. Experienced in marketing analytics or customer behavior modeling.  
  • 5 to 7 years of experience in data science, including hands-on experience with Machine Learning (e.g., scikit-learn, TensorFlow, PyTorch, DataRobot, Databricks) and Generative Artificial Intelligence. Experience with automated model deployment and monitoring tools. 
  • Possess outstanding analytical, modeling, problem-solving, and critical-thinking skills. 
  • Experienced with cloud platforms such as AWS, Azure, and Google Cloud. Familiar with big data technologies (Spark, Hadoop) 
  • Strong knowledge of machine learning algorithms and their applications in automated systems. Experience with advanced modeling techniques like ensemble methods, time series analysis, and probabilistic modeling 
  • High proficiency in Python or R for statistical analysis, model development, and process automation. Proficient+ with SQL for data extraction and manipulation.  
  • Proficiency with data visualization tools (Power BI, Tableau, or similar) and their automation capabilities

While performing the duties of this job, the employee is frequently required to stand, walk, sit, use hands to finger, handle, or feel, talk, hear and concentrate. Specific vision abilities required by this job include close vision, distance vision, depth perception, and ability to adjust focus.

This job requires the ability to perform duties contained in the job description for this position, including, but not limited to, the above requirements. Reasonable accommodation will be made for otherwise qualified applicants as needed to enable them to fulfill these requirements.

We are committed to ensuring equal employment opportunities for all job applicants and employees. Employment decisions are based upon job-related reasons regardless of an applicant's race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, marital status, genetic information, protected veteran status, or any other status protected by law.

AAA Life Insurance Company does not offer immigration sponsorship for this position. This includes visa types such as H-1B, TN, and STEM OPT. Please do not apply if you currently require or may require employer-sponsored immigration support now or in the future.

#LI-Hybrid

Employment Type: FULL_TIME