KEY RESPONSIBILITIES:
Data Science:
- Developmachine learning modelsto supportrecommendation systemsandNLP projects
- Provide actionable insights forproduct and service optimization
Data Engineering:
- Build and maintainscalable ETL pipelines
- Optimizedata storage solutions(data lakes, columnar formats) and ensuredata accuracyfor analytics
Data Analysis & Insight Generation:
- Analyze complex datasets to uncovertrendsandpatterns
- Generate and present insights that drivestrategic decisionsand enhanceclient services
Stakeholder Collaboration:
- Work withproduct and service teamsto understanddata needsand translate them intotechnical solutions
Working Relationships:
- Reporting to:VP Business Growth
- External Stakeholders:Clients
Skills/Competencies Required:
Technical Skills:
- Proficiency withPython(Pandas, NumPy),SQL, andJava
- Experience withLLMs,Lang Chain, andGenerative AItechnologies
- Familiarity withML frameworks(Tensor Flow, PyTorch) anddata engineering tools(Spark, Kafka)
- Strongdata analysis skillsand ability to present findings to both technical and non-technical stakeholders
- Proficient in keydata engineering concepts, such asdata lakes,columnar formats,ETL tools, andBI tools
- Knowledge inMachine Learning,NLP,Recommender systems,personalization,Segmentation,microservices architecture, andAPI development
- Ability to adapt to afast-paced,dynamic work environmentand quickly learn new technologies
Soft Skills:
- Work well in ateamor independently
- Excellentwritten&verbal communication skills
- Strongcritical thinkingandquestioningskills
- High degree offlexibilitywilling to fill in the gaps rather than relying on others
- Strongcommunicationskills, especially in presentingdata insights
- Flexibility, problem-solving, and aproactive approachin afast-paced environment
Academic Qualifications & Experience Required:
Required Educational Qualification & Relevant Experience:
- Bachelor's DegreeinComputer Science,Data Analytics,Engineering, or a related field
- Minimum3 to 5 yearsof experience indata scienceanddata engineering
- Strongcritical thinkingabilities and capacity to work autonomously
- Proficient understanding of keydata engineering concepts(data lakes, columnar formats, ETL tools, and BI tools)
- Highmotivation,good work ethic, maturity, and personal initiative
- Strongoralandwritten communicationskills
