Alap

Data Scientist

Kreis 2, Zürich, Switzerland Társaság: TN Switzerland Ügyfél / Munkáltató: Manulife
Közzétéve: 18.05.2026
Zárási dátum: 02.07.2026
Munkareferenciák: e9f8e51698ef80a35b20eb71683d2679

Munkaköri információk

Elhelyezkedés
Kreis 2, Zürich, Switzerland
Társaság
TN Switzerland
Ügyfél / Munkáltató
Manulife
Munkareferenciák
e9f8e51698ef80a35b20eb71683d2679
Listázási típus
Alap
EU-s munkavállalási engedély szükséges
Nem
Közzétéve
18.05.2026
Zárási dátum
02.07.2026

Munkaköri leírás

This role provides the opportunity to support analytics‑enabled initiatives by developing and delivering data analysis and models that address defined business needs. As part of the MBPS Advanced Analytics team, the role contributes to Manulife’s mission of helping customers make decisions easier and lives better by producing reliable, actionable insights from data. The successful candidate will work closely with internal teams and business stakeholders to execute analytics tasks across various use cases within the customer lifecycle. Through this role, they will gain hands‑on experience working with real business data, established analytics processes, and end‑to‑end solution delivery.Position Responsibilities• Develop and implement analytics‑enabled solutions to improve business processes, generate insights, and support business strategy• Own and deliver end‑to‑end analytics projects of moderate complexity, while contributing to larger, more complex initiatives• Analyze large and complex datasets to generate actionable insights and translate findings into clear business recommendations• Collaborate closely with business stakeholders and subject matter experts to understand data sources, processes, and business needs• Provide guidance and mentorship to junior data scientists and contribute to knowledge sharing within the analytics communityRequired QualificationsMinimum of 5 years of applicable experience with advanced knowledge of programming languages and concepts (Python and SQL, SQL queries) Knowledge in data visualization tools such as PowerBI, plotly, R Shiny, etc. (or other equivalent data visualization tools) Strong knowledge of machine learning and AI algorithms Advanced degree in Statistics, Mathematics, Computer Science, Engineering, or a related field; or a Bachelor’s degree with equivalent technical experience​Preferred QualificationsExperience applying statistical modeling and machine learning techniques (e.g., regression, clustering, decision trees, survival analysis)Working knowledge of AI, GenAI, or advanced analytics toolkits and frameworks, including exposure to Retrieval‑Augmented Generation (RAG) Exposure to cloud platforms (e.g., Azure, AWS, or GCP) for data processing, model development, or solution deploymentExperience with data visualization tools such as Tableau, Qlik, or open‑source libraries (e.g., ggplot, d3)Familiarity with relational database models and large‑scale data environmentsProficient in querying and analyzing both structured and unstructured data (SQL, NoSQL, JSON, MongoDB) Experience designing or implementing scalable, end‑to‑end analytics processes with appropriate governance and tracking mechanisms​When You Join Our TeamWe’ll empower you to learn and grow the career you want.We’ll recognize and support you in a flexible environment where well‑being and inclusion are more than just words.As part of our global team, we’ll support you in shaping the future you want to see.About Manulife and John HancockManulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit .Manulife is an Equal Opportunity EmployerAt Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact .Working ArrangementHybrid

Képességek

apply blended learning apply for research funding apply research ethics and scientific integrity principles in research activities build recommender systems Business Analytics Business Intelligence collect ICT data communicate with a non-scientific audience Computational Biology Computer Simulation conduct research across disciplines create data models Data Engineering data ethics Data Mining Data Models data quality assessment Data Science data visualisation software define data quality criteria deliver visual presentation of data demonstrate disciplinary expertise design database in the cloud design database scheme develop data processing applications develop professional network with researchers and scientists Digital Curation disseminate results to the scientific community draft scientific or academic papers and technical documentation empirical analysis establish data processes evaluate research activities execute analytical mathematical calculations Hadoop handle data samples Healthcare Analytics image recognition implement data quality processes increase the impact of science on policy and society information categorisation Information Extraction integrate gender dimension in research integrate ICT data interact professionally in research and professional environments interpret current data LDAP LINQ make data-driven decisions manage data manage data collection systems manage findable accessible interoperable and reusable data manage ICT data architecture manage ICT data classification manage intellectual property rights manage open publications manage personal professional development manage research data Marketing Analytics mathematical modelling MDX mentor individuals multidisciplinary research N1QL normalise data online analytical processing operate open source software perform data cleansing perform data mining perform project management perform scientific research promote open innovation in research promote the participation of citizens in scientific and research activities promote the transfer of knowledge publish academic research quantitative analysis query languages report analysis results Research Design resource description framework query language Scientific Computing scientific literature Social Network Analysis SPARQL speak different languages State Estimation statistical modeling techniques Statistics synthesise information teach in academic or vocational contexts think abstractly Unstructured Data use data processing techniques use databases use spreadsheets software visual presentation techniques write scientific publications XQuery

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