Data Job Description
Data Duties & Responsibilities
To write an effective data job description, begin by listing detailed duties, responsibilities and expectations. We have included data job description templates that you can modify and use.
Sample responsibilities for this position include:
Data Qualifications
Qualifications for a job description may include education, certification, and experience.
Licensing or Certifications for Data
List any licenses or certifications required by the position: AWS, CBAP, PMI, ITIL, TQM, SHRM, FISD, TDWI, SAS, CDMP
Education for Data
Typically a job would require a certain level of education.
Employers hiring for the data job most commonly would prefer for their future employee to have a relevant degree such as Bachelor's and Master's Degree in Computer Science, Statistics, Mathematics, Engineering, Information Technology, Science, Business, Economics, Technical, Information Systems
Skills for Data
Desired skills for data include:
Desired experience for data includes:
Data Examples
Data Job Description
- Propose, investigate, develop and refine new analytic capabilities for deployment in the business
- Manipulate and analyze large data sets using industry standard tools and techniques
- Develop and deploy analytics that discover and exploit social networks
- Develop and deploy analytics with heterogeneous data environment
- Representing Reference Data CAMDM and the IB Reference Data Design Authority
- Creating and maintaining our Data Entity standards and interlocking with the CDO offices’
- Creating and maintaining Data Models and capturing and establishing lineages between various models, data requirements, and business requirements
- Creating and Maintain Reference Data CAMDM core design artefacts under changes control
- Creating and maintaining the IB Reference Data service Catalogue
- Effective listener, who can give timely and constructive feedback
- Lead the overall logical / physical database architecture design and control of the organization's physical, relational and object-oriented databases across multiple platforms and computing environments
- Extensive experience in Master Data Management (MDM)
- Financial Services background or experience preferred across different LOBs
- At least 4 - 9 years of experience into SAS
- ETL tools (Kettle, Informatica)
- As needed, may need to qualify for Public Trust – Moderate Risk
Data Job Description
- Responsible for extraction, cleansing, and preparation of data used in predictive and prescriptive modeling within the Operations Division
- Execute and maintain robust processes for extracting and cleaning data for use in descriptive, inferential, and predictive models, support quality reporting of the data itself
- Execute data preparation steps (e.g., concatenations, creating data dictionaries - assigning attributes, data types and specifications) and the archival of data tables
- Maintain seamless data flow across the technology platform
- Actively support data management initiatives by maintaining data definitions, executing regular data acquisition and reporting, and continually advancing the automation of data flow
- Maintain master data tables within the scope of Operations Data Analytics
- Facilitate internal data collection programs and integrate data streams and reporting within a data warehouse environment
- Maintain data flow relative to database changes, new systems and data architecture
- Interact with Operations data owners and stakeholders to maintain efficient and accurate data flow and data reporting technology
- Maintain standard work for data management practices
- BS/BA degree in computer science, MIS or related field
- Prior insurance work related experience in the P&C sector required with commercial P&C a plus
- Minimum 5 years prior experience focused in data analysis, modeling, profiling and mapping
- The ability to decompose complex business and data requirements into technical specifications and data mapping documents
- Prior experience on System's Integration or Data Warehousing projects
- Able to work productively and communicate well in a team environment
Data Job Description
- Developing innovative, scalable machine learning and data mining solutions that mine complex user behavioral data and transform it into actionable insights
- Collaborate with data science team on implementing machine learning algorithms to facilitate audience intelligence and cross-brand personalization initiatives
- Assume proactive verification of database interface and data accuracy
- Verify data format as appropriate for the specific use case as defined by manager and stakeholders
- Maintain manual data collection programs and administer database roles, permissions, and data-entry form accuracy and reliability within the scope of data analysis
- Maintain data dictionaries for process, equipment, tags, and test result data
- Support Data Analytics Manager to present and facilitate meetings adapting content to the different audiences
- Establish open, transparent communication about the data architecture and data management processes
- Maintain effective and timely communication with various stakeholders related to the use of the information by communicating success, concerns, risks, and status updates on related work
- Communicate issues or outages data flow and data quality
- Backfill - Assignment May Extend till 2 years or Convert to Full time
- Strong SQL – joins
- Should have experience in Logical Data Modelling (Data mapping and customization of FSLDM) and Physical Data Modelling
- Should have experience in Analysis, Design, Development and Implementation of Data warehousing solutions (EDW) using Informatica, Teradata
- Understanding of applied machine learning algorithms
- Ability and eagerness to work on a variety of problems such as computer vision and image recognition, recommender systems and other scalable machine learning applications
Data Job Description
- Utilize project methodology to include kick off, requirements, alpha, beta, final review, and user acceptance testing
- Acts as SME for data analytics initiatives and data management
- Provides project executive summary reports, presentations, agendas related to project work
- Establishes rapport with project team members and facilitate a team-based mindset
- Performs Company business in accordance with all regulations and Company policies and procedures
- Under the supervision of a Data Scientist execute data analyses (descriptive, diagnostic, and predictive) on clinical trials and/or diagnostics instruments data
- Support Data Scientists in developing an analytical approach for data-centric services and execute it
- Work closely together with other Data Analysts and exchange knowledge and experience with them
- Have a high-level understanding of or be willing and able to learn how the relevant data generating processes work
- Analyzing massive volumes of data, optimization and performance tuning
- Python, C, or C++
- Experience with data gathering, data wrangling, cleaning, transforming and development of own machine learning models
- Minimum 3-5 years experience with scripting languages
- Advanced SQL skills, including significant PostGres or Redshift
- 3+ years experience with the Linux shell
- 1-2+ years experience writing scripts to retrieve data from REST and/or SOAP APIs
Data Job Description
- Desgning and developing automated test cases that verify solution feasibility and interoperability, including performance assessments
- Providing suggestions on Big Data ingestion strategies from any data source or type
- Delivering implementation on permanent connector which includes data import, transformation, export and synchronization
- 4 – 5 years of extensive experience as Hadoop Developer and Big Data analyst
- In depth understanding and usage of Hadoop Architecture frameworks and various components such as HDFS, Job Tracker, Task Tracker, Name Node
- Responsible for the process of data normalization working closely with the DBA to reach a consensus on the physical data base design
- Document all primary and foreign keys, indexes and constraints
- Generate DDL/Alter table scripts for implementation by the DBAs
- Develop and maintain data pipelines, with a focus on writing scalable, clean, and fault-tolerant code
- Maintain various data stores and distributed systems, such as Hive, Presto and Druid
- Understanding of multivariate statistical techniques, such as Factor analysis, cluster analysis, regression analysis, ANOVA
- Partner with business units in understanding our data environment and capabilities
- Understand and elicit data requirements using interviews, data analysis, business process descriptions, stories, scenarios, business analysis, and workflow analysis
- The individual will act as a liaison between technology teams and internal business units
- The data analyst may also assist in identifying data quality problems and in determining options for how they will be handled
- Function as a subject matter expert on our data, processes, and business methodologies