Specialist Data Scientist , Actimize
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Summary
Data Scientist on the NICE Actimize team in Pune, building predictive and generative ML models to detect fraud and AML compliance risks in large client datasets, from data prep through model deployment and monitoring. Core stack is Python, SQL, Excel, statistical/ML techniques, with Kubernetes and AWS exposure.
Job Summary
Responsibilities
Have you got what it takes
Additional Desired Qualifications
Job Details
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
At NiCE, we don t limit our challenges. We challenge our limits. Always. We re ambitious. We re game changers. And we play to win. We set the highest standards and execute beyond them. And if you re like us, we can offer you the ultimate career opportunity that will light a fire within you.
So What s the role all about
We are looking for talented and motivated Data Scientists who are passionate about solving complex fraud-related problems using advanced analytics and machine learning. You are someone who thrives on exploring large datasets, uncovering hidden patterns, and building predictive models that make a real business impact. You enjoy collaborating with cross-functional teams, experimenting with new techniques, and delivering scalable analytical solutions.
If you love transforming raw data into actionable insights and want to be part of a high-performing analytics team at NICE Actimize, this role is for you.
Responsibilities
- Analyzing large volumes of client data to extract actionable insights, assess AML compliance and identify and flag inconsistencies or potential compliance risks.
- Develop and execute advanced analytics projects from end to end, including data collection, preprocessing, model development, evaluation, and deployment.
- Design and develop predictive and generative models to extract actionable insights from large and complex datasets.
- Utilize statistical techniques and quantitative analysis to identify trends, patterns, and correlations within the data.
- Translate business problems into analytical solutions in partnership with Product, Engineering, and domain SMEs.
- Stay abreast of the latest advancements in Data Science, Machine Learning, Generative AI and recommend innovative approaches to solve business challenges.
- Proficiency in handling imperfections in data is an important aspect of this role
- Staying informed about developments in Data Science and adjacent fields to ensure that outputs are always relevant and drive the continuous improvement of Ways of Working of the Data Science and analytics
- Bring together disparate data types in compelling visualization packages that provide end users with the ability to see both the landscape and details leading to improved decision-making Presenting results in a clear manner
- Exceptional technical and business communication in English, verbal and written. Should be good at time management.
- Collaboration- Collaborating with Business and other internal stakeholders within NiCE and should be able to solve data problems in a simple and agile manner.
- Stakeholder Management-
- Ability to explain complex analytical concepts to a non-technical audience.
- Ability to effectively advocate technical solutions to customers/account managers /Data engineering teams and business audiences
- Mentor and support team skill building-
- Mentor and coach other team members to develop technical skills.
- Present innovative solutions to various stakeholders and bring that skill within team to make them future ready
- Should be a good team player to actively contributes to team in order to complete tasks, meet goals, respect ideas and aim to improve the product or process at hand
Have you got what it takes
- 8+ Years of Experience in application and knowledge of statistical techniques and Data Science concepts (statistical tests, regression, feature selection, time series modeling, Advanced Machine Learning etc.)
- Strong experience with using SQL and EXCEL.
- Strong programming skills in Python and ability to rapidly learn new programming tools and experience in application and knowledge of machine learning techniques (clustering, decision trees, boosting, etc.) and their advantages or drawbacks.
- Good command into develops and deploying classification and regression machine learning models at an enterprise level.
- Versed with various bagging boosting methods and able to choose which one should be used based on data.
- Have fair understanding of Logistic regression and various regularization techniques.
- Having knowledge of Model deployment and production model monitoring with ML-ops framework or containerized environment (Kubernetes) will be plus.
- Expert into troubleshooting issues with a variety of production data and past deployed models.
- Familiarity with various cloud infrastructure (especially AWS) is a good to have.
- Ability to work in multi-disciplinary agile teams.
- Strong commitment to deliver work with Right first time approach.
Additional Desired Qualifications
- Experience in development of risk management models, particularly in the AML compliance areas.
- Knowledge of national and international financial systems and appropriate data standards.
- Experience of containerized Model development using Kubernetes.
- Exposure to banking or financial services domain.
- Advanced degree in a quantitative area (statistics, mathematics, physics, computer science, engineering) preferred.
Job Details
- Role Type: Individual Contributor
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.