Βασικό
Data Scientist
Δημοσιεύτηκε: 18.05.2026
Καταληκτική ημερομηνία: 02.07.2026
Αναφορά εργασίας: e9f8e51698ef80a35b20eb71683d2679
Πληροφορίες εργασίας
Τοποθεσία
Kreis 2, Zürich, Switzerland
Εταιρεία
TN Switzerland
Πελάτης / Εργοδότης
Manulife
Αναφορά εργασίας
e9f8e51698ef80a35b20eb71683d2679
Τύπος καταχώρησης
Βασικό
Απαιτείται άδεια εργασίας της ΕΕ
Όχι
Δημοσιεύτηκε
18.05.2026
Καταληκτική ημερομηνία
02.07.2026
Περιγραφή καθηκόντων
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 experiencePreferred 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 mechanismsWhen 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
Δεξιότητες
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