Pay
$118K–$195K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,828 postings in the last year. Stated ranges, not salaries paid.
Senior Data Scientist - BFS
Atlanta, Georgia, United States
Live, first seen by us 28 days ago- Pay
- Pay not listedSimilar roles state $118K–$195K
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
Before you apply
- Employer’s visa record
- 291 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.
What you’ll work on
Full postingDesign, build, and validate ML models for credit risk, fraud, and segmentation
Write clean, modular, production-ready Python for feature engineering and training
Work with MLOps teams to move models into production and track drift
Partner with business stakeholders to refine requirements and deliver solutions
Present findings and business impact to technical and non-technical leaders
From the employer’s posting
Design, build, validate, and optimize cutting-edge machine learning and statistical models
Write clean, modular, production-ready Python code to perform end-to-end data manipulation, feature engineering, model training, and performance evaluation
Collaborate with MLOps and cloud engineering teams to transition models from prototype to scalable production environments, tracking model performance and drift over time
Partner directly with business stakeholders, product managers, and engineering teams to understand business context, refine requirements, and deliver data-driven solutions
Present analytical findings, business impact, and technical methodologies clearly to both technical teams and non-technical business leaders
What you’ll bring
All qualificationsCore experience
- Experience: 6–10 years of experience in Data Science, Advanced Analytics, or Machine Learning roles.
Qualification wording
Experience: 6–10 years of experience in Data Science, Advanced Analytics, or Machine Learning roles.
Education & alternatives
- Data Handling: Strong proficiency in SQL and experience working with large-scale, structured and unstructured datasets. - Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field. Why Join Tiger Analytics:
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 15, 202628 days ago
- Recorded sightings
- 36
- Last seen by us
- Nov 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 28
Similar jobs usually come down between day 8 and day 60.
At Tiger Analytics, jobs usually come down by about day 68.
From 11,606 similar postings that came down, and 27 of Tiger Analytics’s. Coming down is not always a hire.
Tiger Analytics is hiring
74 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Scientist hiring is picking up
- Its jobs tend to stay up a long time
- 1% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- NumPy
- pandas
- PyTorch
- scikit-learn
- TensorFlow
- XGBoost
Where the posting names them
- Model Development & Innovation: Design, build, validate, and optimize cutting-edge machine learning and statistical models (e.g., predictive analytics, credit/risk modeling, fraud detection, customer segmentation) tailored for the financial sector. - Hands-on Execution: Write clean, modular, production-ready Python code to perform end-to-end data manipulation, feature engineering, model training, and performance evaluation. - Client & Stakeholder Engagement: Partner directly with business stakeholders, product managers, and engineering teams to understand business context, refine requirements, and deliver data-driven solutions.
- Domain Expertise: Proven track record working within the Banking or Financial Services industry (e.g., consumer banking, risk analytics, fraud prevention, wealth management, or credit modelling). - Technical Skills: Strong, hands-on proficiency in Python and its scientific ecosystem (e.g., Pandas, NumPy, Scikit-Learn, XGBoost, TensorFlow, or PyTorch). - Modelling Capabilities: Hands-on experience designing and building complex, cutting-edge AI/ML models across the entire development lifecycle.
- Modelling Capabilities: Hands-on experience designing and building complex, cutting-edge AI/ML models across the entire development lifecycle. - Data Handling: Strong proficiency in SQL and experience working with large-scale, structured and unstructured datasets. - Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field.
Your next step
Complete your application on apply.workable.com. The employer’s form will show what is required.
Applying through Workable
- No account needed. You can import your resume to fill in the form, or skip that and fill it in yourself.
Already applied? Track this application
Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
Shape the Future of AI. Transform the World's Leading Businesses.
Tiger Analytics is one of the fastest-growing AI services firms, partnering with some of the world's largest and most influential organizations to redefine how business gets done. We help Fortune 500 companies harness the power of Artificial Intelligence, Generative AI, Data Science, Data Engineering and Advanced Analytics to solve their most complex challenges, unlock new growth opportunities, and create lasting business impact.
We are at the forefront of the AI revolution, helping enterprises move beyond traditional analytics to embrace Generative AI, agentic AI, intelligent automation, and cloud-native data platforms. A global presence across North America, Latin America, Europe, and India
At Tiger Analytics, we don't just help businesses adapt to the future—we help them build it.
We are seeking a hands-on, highly skilled Senior Data Scientist to join our team in Atlanta, GA. In this role, you will work closely with enterprise clients in the Banking and Financial Services sector to design, develop, and deploy cutting-edge machine learning and predictive models. You will be responsible for translating complex financial business challenges into robust AI/ML solutions and writing clean, scalable code.
What you will be doing
- Model Development & Innovation: Design, build, validate, and optimize cutting-edge machine learning and statistical models (e.g., predictive analytics, credit/risk modeling, fraud detection, customer segmentation) tailored for the financial sector.
- Hands-on Execution: Write clean, modular, production-ready Python code to perform end-to-end data manipulation, feature engineering, model training, and performance evaluation.
- Client & Stakeholder Engagement: Partner directly with business stakeholders, product managers, and engineering teams to understand business context, refine requirements, and deliver data-driven solutions.
- Model Operations: Collaborate with MLOps and cloud engineering teams to transition models from prototype to scalable production environments, tracking model performance and drift over time.
- Insights & Communication: Present analytical findings, business impact, and technical methodologies clearly to both technical teams and non-technical business leaders.
Requirements
- Experience: 6–10 years of experience in Data Science, Advanced Analytics, or Machine Learning roles.
- Domain Expertise: Proven track record working within the Banking or Financial Services industry (e.g., consumer banking, risk analytics, fraud prevention, wealth management, or credit modelling).
- Technical Skills: Strong, hands-on proficiency in Python and its scientific ecosystem (e.g., Pandas, NumPy, Scikit-Learn, XGBoost, TensorFlow, or PyTorch).
- Modelling Capabilities: Hands-on experience designing and building complex, cutting-edge AI/ML models across the entire development lifecycle.
- Data Handling: Strong proficiency in SQL and experience working with large-scale, structured and unstructured datasets.
- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field.
Why Join Tiger Analytics:
- Drive High-Impact Business Transformation: Lead strategic engagements that go beyond traditional analytics, delivering enterprise-wide AI adoption, cloud-native data modernisation, and measurable business outcomes.
- Build and Lead at Global Scale: Collaborate with exceptional AI, data, engineering, and consulting talent across geographies to deliver transformative solutions and grow strategic client partnerships.
- Benefits: Medical, Dental, Vision, Retirement Accounts, Long and Short Term Disability, Life Insurance, HSA/FSA Accounts (USA) and Discretionary time off.
- Continuous Learning & AI Upskilling: Stay ahead of the rapidly evolving AI landscape through continuous learning, hands-on exposure to emerging technologies, and opportunities to build expertise in Generative AI, agentic AI, and next-generation data platforms. Grow alongside a team that invests in developing future-ready skills and encourages innovation.
- This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
Benefits
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Atlanta, Georgia, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.