Data Scientist at Experian

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

16 Apr, 26

Salary

0.0

Posted On

16 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Python, SQL, Statistical Modeling, Time Series Forecasting, Generative AI, MLOps, Data Visualization, Cloud Platforms, Model Deployment, Model Monitoring, Predictive Modeling, Data Analysis, Collaboration, Communication

Industry

Information Services

Description

Company Description Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. Job Description We are looking for an experienced and driven Data Scientist to join our team and lead the development of AI-powered solutions. As a Data Scientist, you will work closely with cross-functional teams to design, implement, and deploy data-driven solutions that drive business value. You will play a key role in shaping our data science strategy, mentoring junior team members, and ensuring the robustness and scalability of our models in production environments. What you'll need to bring to the role & Experian · A Bachelor's/Master's/Ph.D. degree in computer science, Statistics, Mathematics, Data Science, or a related field. · 2+ years of experience in data science or machine learning, with a strong track record of delivering impactful solutions. · Proficiency in Python and ML frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar. · Strong understanding of statistical modeling, time series forecasting, supervised and unsupervised learning, and optimization techniques. · Good understanding of generative AI concepts and principles. · Intermediate to fluent English proficiency – technical concepts clearly in English is essential. · Experience working with financial datasets (e.g., credit scoring, fraud detection, risk modeling, pricing, or forecasting). · Proficiency in SQL and experience with relational and non-relational databases (e.g., PostgreSQL, CosmosDB, MongoDB). · Experience deploying models into production using Databricks and cloud platforms (AWS, GCP, or Azure). · Familiarity with MLOps practices, CI/CD pipelines, and model monitoring tools. · Experience with data visualization tools (e.g., Plotly, Tableau) to communicate insights effectively. Work that matters - What you'll be doing · Lead the design, development, and deployment of machine learning models to solve high-impact financial problems. · Collaborate with product managers, engineers, and business stakeholders to define data science use cases and translate them into actionable solutions. · Analyse large-scale structured and unstructured datasets to extract insights and build predictive models. · Develop and maintain robust model training workflows. · Ensure model interpretability, fairness, and compliance with regulatory standards. · Communicate findings and recommendations clearly to both technical and non-technical audiences. More about you · Passion for using data to drive decisions. · A mindset for continuous learning and innovation. · Ethical awareness of bias, fairness, and transparency in AI models. Why this role is important to us This role is critical to our mission of leveraging data and AI to drive innovation across our services. As a Data Scientist, your expertise will directly influence strategic decisions, improve customer outcomes, and enhance operational efficiency. You will collaborate closely with professionals from diverse backgrounds - including product, engineering, operations, and business strategy - to solve real-world challenges across multiple domains. Your insights will help shape our data science roadmap and deliver measurable value to the organization. Qualifications · A Bachelor's/Master's/Ph.D. degree in computer science, Statistics, Mathematics, Data Science, or a related field. · 2+ years of experience in data science or machine learning, with a strong track record of delivering impactful solutions. Additional Information Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why. Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity. Experian Careers - Creating a better tomorrow together Find out what its like to work for Experian by clicking here Employee Status: Regular Role Type: Hybrid Department: Technology Schedule: Full Time

Responsibilities

Lead the design, development, and deployment of machine learning models to solve high-impact financial problems. Collaborate with product managers, engineers, and business stakeholders to define data science use cases and translate them into actionable solutions.