Job Title: Developer – Analytics
Salary: Rs 3.0 Lakhs to ₹ 16.0 Lakhs
Location: Bengaluru, Karnataka
Company: SAP
Qualifications: Bachelor’s degree
Experience: 4+ years
ABOUT SAP
it, centered in Walldorf, Germany, is an international leader in corporation software program answers, serving over 440,000 customers in hundred and eighty nations. Founded in 1972, it’s number one attention is on imparting modern software program programs that assist companies of all sizes manage their operations more successfully.
The agency’s product portfolio spans diverse domain names which include ERP (Enterprise Resource Planning), CRM (Customer Relationship Management), SCM (Supply Chain Management), and more recently, cloud computing offerings via SAP HANA and SAP S/4HANA. it’s answers are vital to enabling virtual transformation and optimizing enterprise techniques across industries which include production, finance, healthcare, and retail.
Job Overview
Sure, as a Developer-Analytics who specializes in analytics, your position includes leveraging statistics to derive insights that inform strategic decisions inside diverse process sectors. You’d analyze tendencies, styles, and metrics to optimize methods, expecting consequences, and pressure commercial enterprise boom. This could consist of growing algorithms, creating statistics visualizations, and participating with stakeholders to apprehend their wishes. Ultimately, your paintings target to decorate efficiency, pick out opportunities, and ensure knowledgeable selection-making across business enterprises.
Qualifications of a Developer – Analytics:
- Technical Skills: Proficiency in programming languages which includes Python, R, SQL, or others relevant to records analysis and manipulation is important. You must be adept at the usage of statistical analysis equipment and frameworks like Pandas, NumPy, SciPy, or machine learning libraries along with Scikit -study or TensorFlow.
- Data Management: Strong information on database structures (SQL, NoSQL) and records warehousing standards. Experience in information extraction, transformation, and loading (ETL) approaches to make certain information integrity and accessibility.
- Data Visualization: Ability to create meaningful visualizations using tools like Tableau, Power BI, or matplotlib/seaborn in Python. This consists of now not only generating charts and graphs but also storytelling through records to carry insights efficiently.
- Analytical Skills: Proficiency in making use of statistical strategies and gadget studying techniques to investigate big datasets. Familiarity with regression evaluation, clustering, class, and time series forecasting.
- Domain Knowledge: Understanding of the industry or domain where analytics are applied (e.g., finance, healthcare, e-trade). Knowledge of applicable metrics, KPIs, and commercial enterprise methods helps in contextualizing record insights.
- Problem-Solving: Strong analytical and important questioning skills to pick out problems, formulate hypotheses, and test answers based on data-driven strategies.
- Communication Skills: Ability to speak complicated technical findings to non-technical stakeholders surely and effectively. This consists of preparing reports, displays, and documentation that articulate insights and suggestions derived from facts evaluation. (Developer – Analytics)
- Continuous Learning: Given the speedy evolution of data technology and strategies, a dedication to staying updated with industry trends and advancements is vital.
Responsibilities of a Developer – Analytics at SAP:
- Data Collection and Integration: Gather statistics from various sources, ensuring its first-rate and compatibility for analysis. This entails collaborating with statistics engineers and stakeholders to define statistics requirements.
- Data Analysis: Clean, process, and examine records to extract meaningful insights. Apply statistical strategies and system-study algorithms to perceive trends, correlations, and styles that drive business decisions.
- Data Visualization: Create visualizations and dashboards that talk about key findings to stakeholders. Ensure those visualizations are intuitive and actionable, assisting choice-making strategies.
- Performance Monitoring: Develop and implement metrics and KPIs to reveal the enterprise’s overall performance. Use analytics to tune progress in the direction of goals and become aware of regions for improvement.
- Predictive Modeling: Build and validate predictive fashions to forecast tendencies, patron conduct, or different commercial enterprise metrics. Evaluate version performance and iterate based on feedback and new data. (Developer )
- Collaboration: Work closely with move-functional groups including enterprise analysts, statistics scientists, and bosses to apprehend commercial enterprise needs and offer statistics-pushed answers.
- Data Governance: Ensure compliance with information privacy regulations and high-quality practices in facts control. Implement records governance policies to preserve records’ satisfaction, safety, and accessibility.
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