Data Scientist

Here is a Data Scientist job description formatted for a careers page. It uses sentence-case headers (with capitalized first letters), includes all key sections, and keeps a clear, professional tone. You can easily adapt this to match your company’s voice or industry.

Data Scientist

About the role

We’re looking for a curious and analytical Data Scientist to join our growing team. In this role, you’ll use data to uncover insights, shape strategies, and improve products. You’ll work closely with engineering, product, and business stakeholders to turn complex data into actionable solutions that drive measurable impact.

We value creativity, rigor, and communication just as much as technical skill.

Key responsibilities

What you’ll be doing

• Analyze large datasets to identify trends, patterns, and actionable insights

• Build predictive models and machine learning pipelines to support product and business goals

• Collaborate with cross-functional teams to frame problems, define metrics, and evaluate outcomes

• Design and run experiments (A/B tests, controlled studies)

• Communicate findings clearly through visualizations, dashboards, and reports

• Work with data engineers to improve data quality, pipelines, and infrastructure

• Help define and promote best practices in data analysis and modeling

Requirements

What you’ll need to succeed

• 3+ years of experience in data science, machine learning, or statistical analysis

• Proficiency in Python or R, and SQL for data manipulation

• Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, XGBoost)

• Solid understanding of statistics, probability, and experimental design

• Strong data visualization skills (e.g., using matplotlib, seaborn, or BI tools)

• Ability to clearly communicate complex ideas to both technical and non-technical audiences

• Familiarity with version control and collaborative workflows

Preferred qualifications

These would be a plus

• Experience working with cloud-based data platforms (e.g., AWS, GCP, or Azure)

• Familiarity with big data tools (e.g., Spark, Hadoop, dbt)

• Exposure to time series forecasting, NLP, or recommendation systems

• Background in product analytics, marketing data, or user behavior modeling

• Graduate degree in a quantitative field such as statistics, computer science, or economics

How to apply

Help us make smarter decisions

To apply, please send:

• Your resume or a link to your LinkedIn profile

• A brief introduction outlining your interest in the role

• Links to relevant projects, GitHub repos, notebooks, or dashboards (if available)

We review applications on a rolling basis. The hiring process includes a technical assessment, a case discussion, and a final interview with team members across data and product.

Would you like a version for Senior Data Scientist, Machine Learning Engineer, or Applied AI Specialist? Let me know!