Role Proficiency:
Independently provides expertise on data analysis techniques using software tools; streamlining business processes and managing team
Outcomes:
- Managing and designing the reporting environment including data sources security and metadata.
- Providing technical expertise on data storage structures data mining and data cleansing.
- Supporting the data warehouse in identifying and revising reporting requirements.
- Supporting initiatives for data integrity and normalization.
- Assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems.
- Synthesize both quantitative and qualitative data into insights
- Generating reports from single or multiple systems.
- Troubleshooting the reporting database environment and reports.
- Understanding business requirements and translating it into executable steps for the team members.
- Identify and recommend new ways to streamline business processes
- Illustrates data graphically and translates complex findings into written text.
- Locating results to help the clients make better decisions. Get feedback from clients and offer to build solutions based on the feedback.
- Review the team’s deliverables before sending final reports to stakeholders.
- Support cross-functional teams with data reports and insights on data.
- Training end users on new reports and dashboards.
- Set FAST goals and provide feedback on FAST goals of reportees
Measures of Outcomes:
- Quality - number of review comments on codes written
- Accountable for data consistency and data quality.
- Number of medium to large custom application data models designed and implemented
- Illustrates data graphically and translates complex findings into written text.
- Number of results located to help clients make informed decisions.
- Attention to detail and level of accuracy.
- Number of business processes changed due to vital analysis.
- Number of Business Intelligent Dashboards developed
- Number of productivity standards defined for project
- Manage team members and review the tasks submitted by team members
- Number of mandatory trainings completed
Outputs Expected:
Determine Specific Data needs:
- Work with departmental managers to outline the specific data needs for each business method analysis project
Management and Strategy:
- Oversees the activities of analyst personnel and ensures the efficient execution of their duties.
Critical business insights:
- Mines the business’s database in search of critical business insights and communicates findings to the relevant departments.
Code:
- Creates efficient and reusable SQL code meant for the improvement
manipulation
and analysis of data.
- Creates efficient and reusable code. Follows coding best practices.
Create/Validate Data Models:
- Builds statistical models; diagnoses
validates
and improves the performance of these models over time.
Predictive analytics:
- Seeks to determine likely outcomes by detecting tendencies in descriptive and diagnostic analysis
Prescriptive analytics:
- Attempts to identify what business action to take
Code Versioning:
- Organize and manage the changes and revisions to code. Use a version control tool like git
bitbucket. etc.
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 to project related reporting standards/process
Skill Examples:
- Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching.
- Communication Skills: Communicate effectively with a diverse population at various organization levels with the right level of detail.
- Critical Thinking: Data analysts must look at the numbers trends and data and come to new conclusions based on the findings.
- Presentation Skills - reports and oral presentations to client
- Strong meeting facilitation skills as well as presentation skills.
- Attention to Detail: Making sure to be vigilant in the analysis to come to correct conclusions.
- Mathematical Skills to estimate numerical data.
- Work in a team environment
- Proactively ask for and offer help
Knowledge Examples:
Knowledge Examples
- Database languages such as SQL
- Programming language such as R or Python
- Analytical tools and languages such as SAS & Mahout.
- Data visualization software such as Tableau or Qlik or Power BI.
- Proficient in mathematics and calculations.
- Spreadsheet tools such as Microsoft Excel or Google Sheets
- Operating Systems and software platforms
- Knowledge about customer domain and also sub domain where problem is solved
Additional Comments:
ROLE: Mid Level Data Scientist REQUIREMENT: • Professional experience of 5-7 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
Python,LLM,GenAI,Machine Learning
