AI/ML Engineer-Data Scientist

Job Description: Expectations from this role:
Experience in LLM and Generative AI
Experience in Document extraction/chat
Strong experience in Python
Experience working in a cloud-native environment such as AWS
Should have hands on experience with AWS Neptune or Neo4J graph database
Experience in building and maintaining open-domain or health care domain-specific ontologies
Understanding of knowledge graphs
Have experience in building graph-based ontology from scratch and working with structured and unstructured data
Experience supporting Client models development on big data infrastructure (on knowledge graph would be a bonus)
Hands on python to build knowledge Graph/ontologies.
Experience with AWS Textract, Comprehend Medical (nice to have)

Expectations from this role:
1. Mining and acquiring 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.
2. Managing master data, including creation, updates, and deletion.
3. Develop reports and analysis that effectively communicate trends, patterns, and predictions using relevant data.Typical performance measures:
26. Schedule adherence to tasks
27. Quality Errors in data interpretation
28. Number of business processes changed due to vital analysis.
29. Number of insights generated for business decisions
30. Customer satisfaction
31. Completion of all mandatory training requirementsPerformance Areas:
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.
2. Communication Skills: Ability to present findings or translate the data into an understandable document
3. Critical Thinking: Ability to look at the numbers, trends, and data; coming up with new conclusions based on the findings.
4. Attention to Detail: Making sure to be vigilant in the analysis to come with accurate conclusions.
5. Mathematical skills to estimate numerical data.
6. Work in a team environment
7. Proactively ask for and offer help Knowledge Examples:
1. Proficient in mathematics and calculations.
2. Spreadsheet tools such as Microsoft Excel or Google Sheets
3. SQL
4. Python
5. DBMS
6. Operating Systems and software platforms
7. Knowledge about customer domain and also sub domain where problem is solved
8. Code version control e.g. git, bitbucket, etc
 

Desired Skills and Experience

AI ENGINEER