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Associate III - Data Science
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Role description
Role Proficiency:
Independently interprets data and analyses results using statistical techniques
Outcomes:
- Independently Mine and acquire data from primary and secondary sources and reorganize the data in a format that can be easily read by either a machine or a person; generating insights and helping clients make better decisions.
- Develop reports and analysis that effectively communicate trends patterns and predictions using relevant data.
- Utilizes historical data sets and planned changes to business models and forecast business trends
- Working alongside teams within the business or the management team to establish business needs.
- Creates visualizations including dashboards flowcharts and graphs to relay business concepts through visuals to colleagues and other relevant stakeholders.
- Set FAST goals
Measures of Outcomes:
- Schedule adherence to tasks
- Quality – Errors in data interpretation and Modelling
- Number of business processes changed due to vital analysis.
- Number of insights generated for business decisions
- Number of stakeholder appreciations/escalations
- Number of customer appreciations
- No: of mandatory trainings completed
Outputs Expected:
Data Mining:
- Acquiring data from various sources
Reorganizing/Filtering data:
- Consider only relevant data from the mined data and convert it into a format which is consistent and analysable.
Analysis:
- Use statistical methods to analyse data and generate useful results.
Create Data Models:
- Use data to create models that depict trends in the customer base and the consumer population as a whole
Create Reports:
- Create reports depicting the trends and behaviours from the analysed data
Document:
- Create documentation for own work as well as perform peer review of documentation of others' work
Manage knowledge:
- Consume and contribute to project related documents
share point
libraries and client universities
Status Reporting:
- Report status of tasks assigned
- Comply with project related reporting standards and process
Code:
- Create efficient and reusable code. Follows coding best practices.
Code Versioning:
- Organize and manage the changes and revisions to code. Use a version control tool like git
bitbucket
etc.
Quality:
- Provide quality assurance of imported data
working with quality assurance analyst if necessary.
Performance Management:
- Set FAST Goals and seek feedback from supervisor
Skill Examples:
- Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching.
- Communication Skills: Ability to present findings or translate the data into an understandable document
- Critical Thinking: Ability to look at the numbers trends and data; coming up with new conclusions based on the findings.
- Attention to Detail: Making sure to be vigilant in the analysis to come with accurate conclusions.
- Quantitative skills - knowledge of statistical methods and data analysis software
- Presentation Skills - reports and oral presentations to senior colleagues
- Mathematical skills to estimate numerical data.
- Work in a team environment
- Proactively ask for and offer help
Knowledge Examples:
Knowledge Examples
- Proficient in mathematics and calculations.
- Spreadsheet tools such as Microsoft Excel or Google Sheets
- Advanced knowledge of Tableau or PowerBI
- SQL
- Python
- DBMS
- Operating Systems and software platforms
- Knowledge about customer domain and also sub domain where problem is solved
- Code version control e.g. git bitbucket etc
Additional Comments:
This SO is created to hire replacement of Mayank Raj (253310) ROLE: Junior Data Scientist REQUIREMENT: • Professional experience of 3-5 years in business analysis, requirement gathering, solution workflow design for AI/ML/Analytics project • Experience in programming skills in Python and SQL • Strong understanding of ML libraries and applications e.g., Time series analysis, Neural Net, SVMs, boosting methods and implementation using Python • Experience in Deep learning techniques • Excellent Communication skills to effectively collaborate with business SMEs, UX team • Intermediate knowledge with Dev Ops practices, including CICD, Automation, Build Management, and Versioning • Understanding of Cloud services, including Microsoft Azure, GCP or Amazon Web Service • Experience in LLM/Gen AI – Prompt Engineering, RAG and parameter hypertuning • Experience in Pyspark will be an added advantage RESPONSIBILITIES: • Excellent problem solving, Critical and Analytical thinking skills and hands on coding skills • Proficient in Data fetch, data merge, data wrangling, exploratory data analysis and feature engineering • Python, SQL Skills with working knowledge of machine learning algorithms • Drive client engagement fully and align the development team towards a technical roadmap • Implements analytical requirements by defining and analysing system problems; designing and testing standards and solutions • Develops solution by preparing and evaluating alternative workflow solutions • Determines operational objectives by studying business functions; gathering information; evaluating output requirements and formats • Designs new analytical solutions by analysing requirements; constructing workflow charts and diagrams; studying system capabilities; writing specifications • Improves systems by studying current practices; designing modifications • Recommends controls by identifying problems; writing improved procedures • Defines project requirements by identifying project milestones, phases, and elements; forming project team; establishing project budget • Monitors project progress by tracking activity; resolving problems; publishing progress reports; recommending actions • Maintains system protocols by writing and updating procedures • Provides references for users by writing and maintaining user documentation; providing help desk support; training users • Maintains user confidence and protects operations by keeping information confidential • Prepares technical reports by collecting, analysing, and summarizing information and trends • Maintains professional and technical knowledge by attending educational workshops; reviewing professional publications; establishing personal networks; benchmarking state-of-the-art practices; participating in professional societies
Skills
Problem Solving,Python,Data Science
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