Data Analytics

Trigent Software Private Limited

Posted: Sept. 26, 2024 Openings: 10 Experience: 2+ Salary: Preferred by Company
Education: B.Sc/ M.Sc/ B.E/ M.E./ B.Com/ M.Com/ BBA/ MBA/B.Tech/ M.Tech/ All Graduates Location: Bangalore
Job Type: Full Time Skills required: Python .net React Native Django Javascript HTML CSS Typescript Communication Skills Power Bi Numpy Pandas Sql machine learning Data Analysis Coimbatore Data Science Java Adobe XD Figma php wordpress Artificial Intelligence Excel

Job description

Position: Application Lead for Data Analytics

As the Application Lead for Data Analytics, you will spearhead the design, development, and configuration of applications, serving as the primary point of contact for all data analytics initiatives.

Key Responsibilities:

Application Development: Lead efforts to design, build, and configure applications focused on data analytics.
Data Analysis: Conduct in-depth analysis of complex data sets using statistical methodologies and data munging techniques to extract actionable insights.
Cross-Functional Collaboration: Work closely with diverse teams, applying expertise in machine learning algorithms, including linear regression, logistic regression, decision trees, and clustering.
Effective Communication: Present technical findings to stakeholders clearly, utilizing data visualization tools such as Tableau or Power BI.
Continuous Learning: Stay current with advancements in machine learning and data science, incorporating innovative techniques to maintain a competitive edge, including familiarity with TensorFlow, Natural Language Processing (NLP), and Big Data technologies.

Required Skills:

Must-Have Skills:
- Strong experience in Data Analytics.
- Solid understanding of statistical analysis and machine learning algorithms.
Good-to-Have Skills:
- Experience with TensorFlow, Natural Language Processing (NLP), and Big Data technologies.
- Proficiency in data visualization tools like Tableau or Power BI.
- Hands-on experience implementing various machine learning algorithms (e.g., linear regression, logistic regression, decision trees, clustering).
- Expertise in data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity.