{"id":3173208,"url":"https://alion.io/job/cognizant-applied-data-scientist","title":"Applied Data Scientist","company":{"id":85,"name":"Cognizant","domain":"cognizant.com","url":"https://alion.io/company/cognizant","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Cognizant Careers","truth_index":{"grade":"A","score":88,"open_postings":136,"ghost_share":0.007,"stale_share":0.632,"repost_share":0.037,"time_to_fill_p50_days":21,"computed_at":"2026-10-26T05:57:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mason, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":130000,"max":150000,"currency":"USD","period":"year","gross":null,"usd_annual":150000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Agile","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Rest-Assured","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-10-23T13:08:54Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-26T14:51:25Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About the role\nAs an Applied Data Scientist, you will make an impact by designing, developing, and implementing AI and machine learning solutions that solve complex business challenges and drive measurable outcomes. You will be a valued member of the AI and Data Science team and work collaboratively with business stakeholders, data engineers, architects, and technology teams to deliver scalable, production-ready solutions.\nIn this role, you will:\nCollaborate with business stakeholders to understand challenges, define requirements, and identify opportunities for AI and machine learning solutions.\nPerform exploratory data analysis, statistical modeling, feature engineering, and machine learning experimentation to generate business insights.\nDesign, develop, test, and deploy machine learning models that address business needs and support decision-making.\nResearch, evaluate, and prototype emerging AI technologies, including generative AI, large language models, and advanced machine learning techniques.\nPartner with cross-functional teams to integrate, monitor, optimize, and maintain machine learning solutions in production environments.\nWork model\nAt Cognizant, we strive to provide flexibility wherever possible, and we are here to support a healthy work-life balance through our various wellbeing programs. Based on this role's business requirements, this is an onsite position requiring 5 days per week in a client or Cognizant office in Mason, Ohio.\nThe working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.\nWhat you need to have to be considered\nProven experience as a Data Scientist, Applied Data Scientist, or Machine Learning Engineer delivering business-focused solutions.\nStrong proficiency in Python or R and experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.\nSolid understanding of statistical analysis, predictive modeling, machine learning algorithms, and data mining techniques.\nExperience developing, deploying, and supporting machine learning solutions in production environments.\nAbility to translate business problems into actionable data science solutions while effectively communicating technical concepts to diverse stakeholders.\nThese will help you stand out\nExperience with generative AI, large language models (LLMs), deep learning, and emerging AI technologies.\nFamiliarity with Azure, Databricks, Spark, Synapse, and Lakehouse architectures.\nExperience deploying machine learning solutions using cloud-native services, Docker, or Kubernetes.\nKnowledge of MLOps practices, model monitoring, performance optimization, and retraining strategies.\nExperience working in Agile, cross-functional delivery environments and presenting analytical findings to non-technical audiences.\nWe're excited to meet people who share our mission and can make 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.\nSalary and Other Compensation:\nApplications will be accepted until November 08, 2026\nThe annual salary for this position is between $ 130,000 - $ 150,000 depending on experience and other qualifications of the successful candidate.\nThis position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.\nBenefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:\nMedical/Dental/Vision/Life Insurance\n\nPaid holidays plus Paid Time Off\n\n401(k) plan and contributions\n\nLong-term/Short-term Disability\n\nPaid Parental Leave\n\nEmployee Stock Purchase Plan\n\nDisclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. 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