Specialist Data Scientist , Actimize

Posted Yesterday
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Pune, Mahārāshtra, IND
In-Office
Senior level
Cloud • Software • Analytics
The Role
Develop end-to-end data science and machine learning solutions for fraud detection and AML compliance. Analyze large datasets, build and deploy predictive and generative models, evaluate model performance, and monitor production models. Collaborate with product, engineering, customers, and domain experts to translate business problems into scalable analytical solutions. Present findings clearly, mentor team members, troubleshoot production data issues, and recommend innovative approaches.
Summary Generated by Built In

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.


How will you make an impact?

You will join a dynamic team of highly skilled Data Scientists and Fraud Analytics experts working on cutting‑edge analytical solutions. In this role, you will:

  • 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. 

What’s in it for you?

Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

 Enjoy NiCE-FLEX!

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.


Requisition ID: 11949

Reporting into: Tech Manager, Actimize

Role Type: Individual Contributor



About NiCE

NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.

Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.

NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.


Skills Required

  • 8+ years of experience applying statistical techniques and data science concepts
  • Strong experience with SQL and Excel
  • Strong Python programming skills
  • Experience with machine learning techniques including clustering, decision trees, boosting, regression, feature selection, and time series modeling
  • Experience developing and deploying enterprise classification and regression models
  • Knowledge of bagging, boosting, logistic regression, and regularization techniques
  • Experience troubleshooting production data and deployed models
  • Ability to work in multidisciplinary agile teams
  • Experience with risk management models, particularly AML compliance
  • Knowledge of national and international financial systems and data standards
  • Experience with containerized model development using Kubernetes
  • Exposure to banking or financial services
  • Advanced degree in statistics, mathematics, physics, computer science, or engineering
  • Knowledge of model deployment, production monitoring, MLOps frameworks, or containerized environments
  • Familiarity with cloud infrastructure, especially AWS

NICE Compensation & Benefits Highlights

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

  • Healthcare Strength — Benefits are described as broad and comprehensive, spanning medical, dental, vision, life, disability, and mental-health support. Added programs like FSA options and fitness stipends contribute to a well-rounded health and wellness offering.
  • Retirement Support — A 401(k) is part of the package, sometimes paired with match details that are described as typical to stronger depending on role and time period. Employee stock participation is also positioned as an additional long-term wealth-building component for eligible roles.
  • Flexible Benefits — Flexible work arrangements are emphasized, including hybrid setups and remote options for some roles. Flex scheduling, paid holidays, and paid sick time add to the perceived flexibility of the overall rewards package.

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The Company
HQ: Hoboken, NJ
10,130 Employees
Year Founded: 1986

What We Do

NICE (Nasdaq: NICE) is the worldwide leading provider of both cloud and on-premises enterprise software solutions that empower organizations to make smarter decisions based on advanced analytics of structured and unstructured data. NICE helps organizations of all sizes deliver better customer service, ensure compliance, combat fraud and safeguard citizens. Over 25,000 organizations in more than 150 countries, including over 85 of the Fortune 100 companies, are using NICE solutions. www.nice.com.

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