Data Scientist

At Shipt, we are transforming the shopping experience and giving time back to consumers. Shipt Shoppers handpick everything from fresh groceries to household essentials, then deliver them to your door in as little as one hour.

Make sure to apply with all the requested information, as laid out in the job overview below.

In the role of Data Scientist, you will be at the forefront of enhancing our analytical approaches and methodologies. This position is not just about managing data;

it's about uncovering insights that drive innovation and efficiency in our marketplace, particularly focusing on supply chain and delivery optimization.

You'll lead in crafting and implementing robust analytical frameworks, providing critical insights into our customer experiences, and playing a key role in decision-making processes that affect the marketplace.

Your work will directly contribute to Shipt’s continuous growth and success, leveraging your expertise in statistical analysis, machine learning, and Python programming to make a lasting impact.

As a member of our team, you will be part of an inclusive, forward-thinking culture that values intellectual curiosity, technical rigor, and collaborative problem-solving.

If you are passionate about leveraging data to create real-world solutions and drive business success, Shipt offers a challenging and rewarding environment where your contributions will be valued and make a difference.

Responsibilities

• Solve ambiguous business problems using data-driven approaches, focusing on supply chain and delivery optimization.
• Create frameworks for decision-making, emphasizing risk management, geospatial data, and logistics.
• Analyze customer experiences to drive revenue, retention, and profitability, using insights from supply chain and geospatial data.
• Evaluate marketplace app changes using A / B tests, quasi-experiments, and causal impact analysis, focusing on delivery and logistics.
• Collaborate on supply chain, delivery, and geospatial analysis projects, sharing techniques and auditing code.
• Work with teams across the company to interpret findings and assess feature impacts.
• Stay updated on supply chain and geospatial data analysis trends.

Requirements

• BA / BS degree or Graduate degree in economics, econometrics, statistics, computer science, or other quantitative fields.
• 2+ years of working experience with statistical inference, experimentation, and predictive modeling.
• Strong machine learning modeling (supervised learning) knowledge.
• Strong SQL skills (Spark, Snowflake, Postgres, Hive, Redshift, etc).
• Coding experience in Python.
• Proficiency in tools like Tableau or Looker for visualizing and reporting data insights.
• Ability to work collaboratively in a dynamic, team-based environment and communicate results to diverse stakeholders.

Good-to-Have

• Proficiency in geospatial data analysis (e.g., Geopandas).
• Experience in risk management and modeling in supply chain or logistics.
• Experience in building tools like Streamlit or other dashboarding applications.

Work Arrangement

Shipt considers candidates located near a Shipt office or workspace in Birmingham, San Francisco, or Minneapolis to be hybrid, which means that they have the flexibility to work from home (with leader approval) or at a Shipt office in order to facilitate the ability to innovate, collaborate, and spark team connections.

In-office expectations will vary by role and leader. Certain roles may require in-office presence on a full-time basis. Please work with your recruiter to learn more about the classification of this role.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or any other characteristic protected by law.

Please inform your recruiting contact upon initial connection if you need any accommodations.

J-18808-Ljbffr