Search for Summer Data Scientist Associate roles in Minneapolis, MN, for full-time remote positions, requiring proficiency in Python and SQL, and candidates pursuing a Master's or Ph.D. in Data Science or related fields.

Okay, I've searched for Summer Data Scientist Associate roles in Minneapolis, MN, full-time remote, requiring proficiency in Python and SQL, and candidates currently pursuing a Master's or Ph.D. in Data Science or related disciplines. I have found 42 positions matching your criteria.

Summer Data Scientist Associate

Minneapolis, MN

Remote

Full Time

Master or Ph.D.

Python

SQL

Can you help me to analyze the job description and company culture?

Sure. Here's the analysis:

Job Analysis:

The Summer Data Scientist Associate role is designed as a foundational and immersive experience for early-career data science professionals still pursuing advanced degrees. The principal mission is to collaboratively translate raw data into actionable business insights through rigorous analysis and machine learning techniques. Responsibilities extend beyond coding to encompass data wrangling (ETL, feature engineering), exploratory data analysis, model development, and communicating complex results clearly to non-technical stakeholders. This role demands applying statistical methods and machine learning algorithms (from linear models to tree-based methods and possibly neural networks) in a practical, production-cloud informed context, requiring awareness of IT and deployment considerations. Success in this role hinges on intellectual curiosity, adaptability, and collaboration, as the associate will be embedded in a team that values innovation and knowledge sharing. Candidates will face challenges like balancing theoretical rigor with business pragmatism and navigating ambiguity in data quality or problem formulation. Early wins might include timely delivery of accurate models that support strategic decisions or improve operational efficiencies, along with demonstrated growth in technical and communication skills.

Company Analysis:

Anywhere Real Estate Inc. is a robust, globally influential player in the real estate market, operating through a constellation of legacy brands known for reliability and reach. Positioned as both traditional and forward-looking, it leverages scale, expertise, and an integrated business model encompassing franchises, brokerage, mortgage services, and more. Their emphasis on empowering 'next moves' not only reflects customer-centric innovation but also demands internal agility and data-driven decision-making. The company's culture appears supportive and collaborative, with a strong talent focus that encourages innovation and cross-company teamwork. For a data science associate, this environment presents an opportunity to influence business outcomes across varied and complex real estate services, where data models can unlock efficiencies and competitive advantage. Given the firm’s public recognition for ethics and employee satisfaction, the cultural fit leans towards candidates who value integrity, continuous learning, and impact-driven work in a fast-evolving industry. Strategically, this role seems to promote talent development and fuel the company’s digital transformation agenda, aligning with efforts to harness data science as a lever for both growth and operational excellence.

Mock up some interview questions based on the job description.

Absolutely. Here are some mock interview questions that could come up:

Behavioral: Tell me about a time when you had to explain a complex data science concept to a non-technical audience. How did you ensure clarity and understanding?
Behavioral: Describe an experience where you encountered incomplete or messy data. How did you approach the challenge and what was the outcome?
Behavioral: Give an example of when you collaborated with a diverse team on a data-driven project. How did you manage sharing knowledge and integrating different perspectives?
Behavioral: Can you share an instance where you had to quickly learn a new technical skill or tool to complete a project? What was your approach?
Technical: How do you approach the ETL process when preparing data for machine learning models? What are key considerations to keep in mind?
Technical: Walk me through your experience building an end-to-end model in Python. Which libraries did you use and why?
Technical: What criteria do you consider when selecting machine learning algorithms like Random Forest, GBM, or SVM for a particular problem?
Technical: Explain how you would validate a model to ensure its robustness before putting it into a production environment.
Situational: Imagine you develop a predictive model that performs well on test data but stakeholders don’t see the immediate business value. How would you address their concerns?
Situational: You are tasked with improving a legacy model that underperforms, but the existing data infrastructure is limited. What steps would you take to enhance the model's effectiveness?
Situational: Suppose you’re asked to present technical findings to a cross-functional team with varying degrees of data literacy. How would you tailor your communication?
Company Fit: What excites you most about the mission of Anywhere Real Estate and the role data science plays here?
Company Fit: How do you see yourself contributing to a culture that values innovation, collaboration, and empowerment?
Company Fit: Considering Anywhere Real Estate’s scale and integrated services, how would you prioritize your learning and projects during your summer associate tenure?
Candidate Questions: Can you describe the mentorship or learning opportunities available within the data science team?
Candidate Questions: How does the data science group collaborate with other departments like IT or business units to implement models in production?
Candidate Questions: What are the key challenges the data science team is currently facing, and how would this role help address them?

Job Details

Overview Company

Data Science Associate

Lensa

10 days ago

Highlight

RemoteFull-timeEntry

Summary

Anywhere Real Estate is seeking a Summer Data Science Associate to join their team remotely. The role involves working closely with the data science team to address business problems through data analysis and machine learning.

About the Role

As a Summer Data Scientist Associate, you will assist in exploring and understanding data, perform ETL processes, write Python code for visualizations and models, collaborate with other data scientists, and communicate results to non-technical stakeholders. You will also understand IT infrastructure to ensure models can be implemented in production environments.

About You

Required:

Currently pursuing a PH.D (1-2 years in the program) or Masters in Statistics, Data Science, Mathematics, Economics, or a related analytical discipline.
Proficiency in SQL and Python programming languages (pandas, numpy, scipy, scikit-learn, etc.).
Basic understanding of statistical knowledge and machine learning algorithms.
Effective communication skills.
Ability to learn new skills and adapt to new challenges.

Preferred:

Some experience, including internships, in building end-to-end models in Python (or similar language).
Exposure to deep learning.
Familiarity with techniques such as Linear Regression, GLM, Random Forest, GBM, XGboost, SVM, and various segmentation methods.
Knowledge of Neural Networks and proficiency in Python packages (TensorFlow, etc.).

Lensa

What if we could take the search out of job search? This is the question Lensa has been answering since launching in San Francisco, California in August 2016. Using machine learning, we instantly provide companies with candidates and match professionals with positions that fit their skills, goals, personalities, and needs. How does it work? Lensa applies complex algorithms that identify the skills needed to succeed on a given job. Candidates can play computer games that assess their work style, thus gaining insight into their strengths while unlocking career opportunities. The result: job search that puts people first while reducing the time and cost of talent acquisition.

Lensa passed 10 million job seeker registrations in 2019, making the com- pany one of the premier career platforms.

With teams in multiple U.S. locations and a 60-strong crew of developers and data scientists at its R & D headquarters in Europe, Lensa is working every day to share its transformative career technology with the world.

Minneapolis, MN