$60 - $70 per hour
Our client is seeking an experienced Analytics Engineer to join its growing Data & Analytics team. This role is ideal for someone who enjoys solving business problems through data, partnering directly with stakeholders a…
Engineering & IT · Fort Worth, TX
Data Scientist jobs in Fort Worth, TX
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
415
Open roles today
$38–$93/hr
Typical pay range
$126k
Median, full-time
7
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01
Open data scientist roles
12 shown of 415 · sorted by freshness
$50 - $55 per hour
Position:Azure Data Engineer Location: Fort Worth, Texas (Hybrid) Duration:3+ months Contract-To-Hire Job ID: 178846 Job Overview... ...data integration and analytics. ~Collaborate with data scientists, analysts, and oth…
$33 per hour
The Project Planning Analyst will support the Supply Chain Strategy and Technology team with project coordination, system testing, data cleanup, electronic document organization, and initiative tracking. This position wi…
Project Engineer Data Center MEP Location: Fort worth, TX Job Type: Long term contract Shift 1- Day Shift (7:00 AM 4:30 PM) Shift 2- (Swing Shift 3:30pm-1:00am) Key Requirements ~ Bachelor's degree required. ~ Support on…
Job Overview: Join the Data Center team within the Cloud Engineering Platforms organization, where you will design, deploy, maintain, and optimize the physical and logical infrastructure within data centers. This role is…
Project Planning Analyst. You will play a critical role in driving the success of our strategic initiatives by supporting system testing, data management, and document organization. This contract position offers exposure…
Our team brings expertise across artificial intelligence and data, digital experience, and platform engineering, enabling the organizations... ...time zones. About the Role We're looking for a Data Scientist to support a…
excellence, you will focus relentlessly on delivering unrivaled digital products that drive a more reliable and profitable airline. The Data Domain refers to the area within Information Technology that focuses on managin…
$90 - $100 per hour
Job Title: Data Scientist – Machine Learning & Generative AI Location:Fort Worth, TX 76155 (Hybrid) Durations: 6-12+ Months with possible extension and conversions. Job Overview: We are seeking a Data Scientist to suppor…
$72.6k - $89.7k
initiatives related to commercialization, scaling, and process improvement. Who Are You ~ Bachelor’s degree in Business, Finance, Data Analytics, Computer Science, or a related field. ~2–4 years in business development,…
$92.41k - $171.13k
Req ID: 382594 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are…
Analyst Position Type: W2 Contract-No Benefits Position Location: Fort Worth, TX Description: Role Overview Seeking a Data Analytics / Business Intelligence professional (3–5 years experience) to design and maintain posi…
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What data scientists earn in Fort Worth
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $38–$51 | $78k–$107k |
| Mid level | $51–$70 | $107k–$146k |
| Senior | $68–$93 | $141k–$194k |
Adjusted for the Fort Worth market from national ranges.
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What employers ask for
The skills these listings keep naming
Python (pandas, scikit-learn)SQLStatistics and A/B testingMachine learning fundamentalsData visualizationExperiment designCommunicating with stakeholdersDomain and product sense
04
Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Walk me through a data project that changed a decision.
Structure it as question, approach, finding, action. Projects that ended in a decision — even 'we did not launch' — beat technically impressive analyses that went nowhere.
How would you design an A/B test for a new feature?
Cover the metric, randomization unit, sample size, and duration, plus a pitfall like peeking or interference. Practical rigor is what is being tested.
Your model performs well offline but poorly in production. Why might that be?
Discuss train/serve skew, data leakage, distribution shift, and feedback loops. Listing several plausible causes and how you would check each is the strong answer.
Explain p-values or confidence intervals to a non-technical stakeholder.
Use plain language and a concrete scenario, and resist overstating certainty. They are testing whether your statistics survive translation.
How do you handle missing or messy data?
First ask why it is missing — the mechanism matters more than the imputation method. Then discuss options and how the choice affects conclusions.
When would you not use machine learning for a problem?
When a rule, a query, or a simple heuristic wins on cost and interpretability. Knowing when ML is overkill signals maturity.
How do you decide which metric a team should optimize?
Talk about proxy versus true goals, gameability, and counter-metrics. A story about a metric that backfired is very effective here.
05
Resume tips that move the needle
For data scientists specifically — generic advice costs you here
01
Lead every bullet with the business result — revenue, retention, cost — and put the method second.
02
Specify your stack concretely: Python libraries, SQL dialects, experimentation platforms, and any production ML experience.
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Distinguish shipped work from research; 'model serving 2M users' and 'notebook analysis' are different claims.
04
Keep one or two public projects or publications linkable, tailored to the industry you are targeting.
05
Name the size and kind of data you worked with — event streams, tabular, text — so teams can map you to their problems.
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Where this role goes
Typical progression
01
Junior Data Scientist
02
Data Scientist
03
Senior Data Scientist
04
Staff Data Scientist
05
Head of Data Science
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