Data Scientist (Hybrid)

Overview:

We are looking for a talented and experienced Data Scientist to join our dynamic team. As a Data

Scientist, you will leverage your analytical skills and expertise in machine learning to extract insights from

complex datasets and drive data-driven decision-making across our organization. You will collaborate

closely with cross-functional teams to develop predictive models, uncover actionable insights, and solve

challenging business problems.

Responsibilities

Data Analysis and Exploration

• Analyze large, complex datasets to identify trends, patterns, and relationships.

• Conduct exploratory data analysis (EDA) to gain insights and formulate hypotheses.

• Utilize statistical methods and data visualization techniques to communicate findings effectively.

Predictive Modeling and Machine Learning

• Develop and deploy predictive models using machine learning algorithms.

• Perform feature engineering, model selection, and hyperparameter tuning to optimize model

performance.

• Evaluate model accuracy, precision, recall, and other performance metrics.

Data Mining and Pattern Recognition

• Apply data mining techniques to extract actionable insights from structured and unstructured

data.

• Identify patterns and anomalies in data to detect fraud, predict customer behavior, or optimize

business processes.

• Implement clustering, classification, regression, and other machine learning algorithms as

needed.

Experimentation and A/B Testing

• Design and conduct experiments to test hypotheses and validate model assumptions.

• Implement A/B testing frameworks to evaluate the impact of changes and interventions.

• Analyze experimental results and provide recommendations for further optimization.

Collaboration and Communication

• Collaborate with cross-functional teams, including engineers, product managers, and business

stakeholders.

• Translate technical findings into actionable insights and recommendations for non-technical

audiences.

• Present findings and proposals in clear, concise, and compelling ways.

Requirements:

• Advanced degree (Master's or Ph.D.) in Computer Science, Physics, Statistics, Mathematics, Economics,

or related field.

• Proven experience in data science, machine learning, or predictive analytics roles.

• Proficiency in programming languages commonly used in data science (e.g., Python, R, etc.).

• Strong understanding of statistical analysis, hypothesis testing, and experimental design.

• Experience with machine learning libraries and frameworks (e.g., TensorFlow, scikit-learn,

PyTorch, etc.).

• Familiarity with data visualization tools and techniques (e.g., Matplotlib, ggplot, Tableau, etc.).

• Excellent problem-solving and analytical skills with attention to detail.

• Effective communication and collaboration abilities in a team environment.

• Ability to manage multiple projects and prioritize tasks effectively.

Work model

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.

What you need to have to be considered

• List the most important qualifications in descending order
• Top 5 most important contributions in descending order
  • Only go beyond 5 if absolutely necessary
  • Be concise but informative
  • Related duties should be combined

These will help you stand out

• List the most important nice-to-haves in descending order
• Top 5 most important contributions in descending order
  • Only go beyond 5 if absolutely necessary
  • Be concise but informative

We're excited to meet people who share our mission and can m

an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.

Total compensation

We regularly assess market data to ensure we offer a competitive compensation package for our associates. The base salary for this position ranges between $75000– $115000 per year. Where the successful candidate may fall within the range depends on relevant education, work and/or management experience and other business-related and job-necessary qualifications. This position is also eligible for Cognizant’s discretionary annual performance-based bonus, as well as benefits that support your physical, mental and financial wellbeing

Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.

Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.

Applicants for US based positions must be currently authorized to work for any employer in the United States. The company is unable to provide employment-based immigration sponsorship for US based positions.

If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email CareersNA2@cognizant.com for roles based in the Americas or CareersIndia2@cognizant.com for roles based in India.

About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.