Senior Data Scientist - BFS

Posted Yesterday
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Atlanta, GA, USA
In-Office
Senior level
Big Data • Analytics • Business Intelligence • Big Data Analytics
The Role
Develop and deploy machine learning and predictive models for banking and financial services clients. Responsibilities include feature engineering, model training and validation, credit and risk modeling, fraud detection, production-ready Python development, stakeholder engagement, MLOps collaboration, model monitoring, and communicating technical findings and business impact.
Summary Generated by Built In

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.

Skills Required

  • 6-10 years of experience in Data Science, Advanced Analytics, or Machine Learning roles
  • Professional experience in the Banking or Financial Services industry
  • Hands-on proficiency in Python and scientific libraries such as Pandas, NumPy, Scikit-Learn, XGBoost, TensorFlow, or PyTorch
  • Experience designing and building complex AI and machine learning models across the development lifecycle
  • Strong SQL proficiency and experience with large-scale structured and unstructured datasets
  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field

Tiger Analytics Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Tiger Analytics and has not been reviewed or approved by Tiger Analytics.

  • Fair & Transparent Compensation — Feedback suggests pay is viewed as fair and market-aligned for many roles and geographies. Consistent, on-time pay and competitive packages in key markets reinforce a generally positive baseline.
  • Healthcare Strength — Feedback suggests U.S. medical coverage is strong, with administration via a known benefits platform and plan options seen positively. Health insurance is often regarded as a bright spot within the package.
  • Leave & Time Off Breadth — Feedback suggests generous PTO, paid sick days and holidays, and flexible PTO alongside remote-work options. These elements indicate broad time-off provisions available on paper.

Tiger Analytics Insights

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The Company
HQ: Santa Clara, CA
5,000 Employees
Year Founded: 2011

What We Do

Tiger Analytics is a global leader in AI and Analytics, helping Fortune 1000 companies solve their toughest challenges. We offer fullstack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. We are Great Place to Work-Certified™ and have been recognized by analyst firms such as Forrester, Gartner, Everest, ISG, HFS, and others. Ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine. In India, our offices are located in Chennai, Hyderabad and Bangalore.

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