Job Overview

This Data Scientist role in Tulsa, OK focuses on turning raw data into actionable insights. You'll work with structured and unstructured datasets, building models that solve real business problems. The environment is collaborative but independent ; you're expected to own your projects from exploration to deployment.

Duties & Responsibilities / JobXi / Tulsa, OK

Clean and preprocess large datasets from multiple sources ; this takes up more time than most people expect.
Develop predictive models using regression, classification, and clustering techniques. You'll test and iterate until the performance is solid.
Present findings to non technical stakeholders in a way they actually understand. That means fewer charts, more story.
Collaborate with engineers to put models into production. You won't just hand over Jupyter notebooks ; you'll help deploy them.
Run A/B tests and statistical analyses to validate hypotheses about user behavior or product changes.

Requirements / JobXi / Tulsa, OK

Skills: Proficient in Python or R for data manipulation. Solid grasp of SQL for querying databases. Experience with machine learning libraries like scikit learn, TensorFlow, or PyTorch.
Experience: Typically 2 5 years in a data science or analytics role. Internships count if the project work was substantial.
Education: Bachelor's degree in statistics, mathematics, computer science, or a related field is common. Master's helps but isn't mandatory if experience compensates.
Mental demands: This role requires focus during long analysis sessions ; debugging a model can be mentally draining. Patience is key when dealing with messy data or vague requirements from teams who don't know what they want until they see it.

What It's Like In This Role / JobXi / Tulsa, OK

The environment varies by employer, but most data scientist roles involve sitting at a desk with dual monitors ; one for code, one for results visualization. Teams are often small; you might be the only quant person reporting directly to a product manager who doesn't speak statistics fluently. That means you'll need to explain why your model matters without using jargon. Tools vary widely: some shops use AWS SageMaker exclusively; others rely on local workstations because their data can't leave premises due to compliance rules (common in healthcare and finance). Schedule is generally 9 to 5ish unless there's an urgent deadline around quarterly planning cycles ; then evenings happen occasionally.

Why You'll Like This Opportunity

The work itself rarely gets boring ; new data brings new puzzles every week. Most companies let you move fast when learning: want to try Bayesian methods instead of standard logistic regression? Go ahead if it fits the problem scope. There's genuine upward mobility across many employers once you've shipped something measurable (like bumping conversion rates 5%). And since employers range from startups to insurance firms in Tulsa, OK, you get exposure to different industries without relocating necessarily.

Schedule & Work Type

Schedules tend toward full time permanent roles rather than contract gigs for data scientists right now ; though remote options exist depending on the specific employer near Tulsa, OK. Onsite hybrid arrangements are common: maybe Tuesdays through Thursdays at an office while Mondays and Fridays stay open for focused work at home where interruptions stop mattering less (until Slack dings anyway). Some positions lean entirely remote still; just check individual postings since policies keep shifting unpredictably month after month lately.

Data Scientist

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