לוח משרות דרושים Data Analyst משרה מלאה

Requirements:
* Vast knowledge of SQL - a must.
* At least 3 years of experience as a Product/Business/ data analyst from an online company - a must.
* BA/B.Sc. in industrial/information systems engineering, Computer Science, statistics or equivalent - a must.
* Experience with AB TEST methodologies - a must.
* Experience working with product managers and cross-functional teams.
* Team players who have excellent communication skills.
* Experience with Tableau At Fiverr, were not about checklists. If you dont meet 100% of the requirements for this role but still feel passionate about the position and think you have the right skills and qualifications to excel at it, we want to hear from you.

Requirements:
Education: Currently in Second year of an Industrial Engineering program at a university, or a recent graduate who is pursuing a second degree. An advantage will be given to candidates with experience in project management roles.
Project management courses or certification - advantage
Technical Skills: Basic proficiency in data analysis and dashboard development tools, preferred experience in Tableau, Databricks, PowerBI, Python and GitHub.
Analytical Skills: Strong analytical thinking and problem-solving abilities.
Languages & Communication: Excellent proficiency in English - verbal & written, crucial for effective communication in reporting findings and team collaboration.
Team player with the ability to drive action without direct authority.
Time Management: Ability to manage tasks effectively and meet deadlines in a fast-paced environment.

Requirements:
Skills
Experience in Data Analysis: Exploration, Cleaning and Preparation - An advantage
Experience in Statistical Analysis - Understanding statistical tests and tools is an advantage
Experience Creating Dashboards and Reports - An advantage
Excel - High level
Programming - Knowledge of programming languages, especially Python or another powerful language for statistical analysis and data visualization - An advantage
Requirements
Third-year bachelor's degree in Industrial Engineering
Availability for three days a week - A must. More is an advantage
The position located in Kiryat Gat.

Requirements:
5+ Years of expiriance in a data analysis - Must.
Experience From a FMCG Company - An Advantage.
Experience working in front of Sales, Trade and Marketing departemnts.
Advence Excel skills and knowledge - Must.
High system proficiency (Power BI, SAP) - an advantage.
Experience in revenue growth and trade spend optimization.
Proven knowledge of promotional planning & ROI Analysis.
Experience in Commercial Forecasting & Budgeting.
Financial Modeling & P&L Understanding.
Our Benefits & Perks:
Careers with caring built in - discover our benefits here.

Requirements:
At least 2 years of hands-on experience working within or alongside data science and engineering teams, providing valuable insights into engineering processes.
Strong background in statistics, machine learning, or actuarial science, enabling effective navigation of complex analytical concepts within an engineering context.
Proven ability to write precise and unambiguous functional requirements that effectively guide engineering development.
Comfort interfacing with both technical engineering teams and customer stakeholders, fostering effective communication across diverse groups.
A pragmatic, delivery-oriented mindset focused on achieving project goals efficiently while maintaining quality.
A proactive problem-solver with the ability to adapt to evolving priorities and initiatives in a dynamic engineering environment

Requirements:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field
2+ years of proven experience developing large-scale software using an object-oriented or functional language.
5+ years of professional experience in data engineering, focusing on building and maintaining data pipelines and data warehouses
Strong experience with Spark, Scala, and Python, including the ability to write high-performance, maintainable code
Experience with AWS services, including EC2, S3, Athena, Kinesis/Firehose Lambda and EMR
Familiarity with data warehousing concepts and technologies, such as columnar storage, data lakes, and SQL
Experience with data pipeline orchestration and scheduling using tools such as Airflow
Strong problem-solving skills and the ability to work independently as well as part of a team
High-level English - a must.
A team player with excellent collaboration skills.

Requirements:
What we need to see:

Bachelors degree in Computer Science, Information Systems, or a related field, or equivalent experience.

A minimum of 10+ years of consistent experience in implementing full-cycle business intelligence projects, including requirements gathering, modeling, data warehousing, data development and creating analytics in visualization applications.

Expert-level knowledge of SQL with the ability to write complex queries and stored procedures efficiently.

Hands-on experience with at least one of the visualization tools like Tableau or Power BI.

Experience with cloud data platforms such as Snowflake or Databricks

A portfolio of successful Business Intelligence projects or case studies.

Excellent written and verbal English language skills.


Ways to stand out from the crowd:

Functional knowledge of Operations and Supply Chain domains.

Hands-on experience with Python and PySpark for large-scale data processing, including experience with distributed computing and data transformation pipelines

Experience with LLMs, embeddings, vector databases or RAG workflows, implementation of AI solutions / algorithms for advanced data analysis - an advantage

A proven track record of designing complex data architectures and successfully implementing new technologies

Proficiency in Jira.

Requirements:
What we need to see:

Bachelors or masters degree in data science, Electrical Engineering, Industrial Engineering, Computer Science, or related field or equivalent experience.

8+ years of experience in a data analytics role, preferably in a high-volume electronics hardware environment.

5+ years proven experience in data collection and statistical analysis for high-volume products datasets.

Proficiency in big data platforms, and statistical analysis tools; skilled in data visualization (e.g., Power BI).

Ways to stand out from the crowd:

Proven experience with AI-driven tools, LLMs and machine learning.

Strong integration capabilities.

Ability to operate independently and influence cross-functional teams without direct authority.

Results-oriented, organized, and detail-driven.

Requirements:
+2 years of practical experience as a Salesforce administrator and implementer.
A solid understanding of business processes.
Experience managing Information Systems projects and application implementation.
Ability to translate business requirements into technical designs.
Excellent interpersonal skills and a team player.
Strong self-learning abilities.
Good analytical skills.
Excellent verbal and written communication skills in English.
Creative thinking and cognitive flexibility.

Requirements:
Expert SQL Mastery: You are a SQL power-user. You enjoy solving complex logic puzzles using code and care deeply about query efficiency and data accuracy.
The "Bridge" Mindset: You can sit in a meeting with a Product Manager to understand a business need, and then translate that into a technical data structure that serves that need.
Logical Architecture: You have a natural talent for organizing information. You know how to build a table that is intuitive and easy for other analysts to query.
Product & Business Acumen: You understand SaaS metrics (ARR, funnels, activation, etc.) and how data logic impacts product growth and strategy.
Experience with Analytics Tools: Proficiency in BI tools (Looker, Tableau, etc.) and a strong understanding of how data flows from technical logs to the end-user interface.
Degree: B.Sc. in Industrial Engineering, Information Systems, Economics, Computer Science or a related quantitative field.
Experience: 1+ years of prior experience in a relevant analytics/technical role

Requirements:
5+ years of experience in data product management or equivalent technical product roles or solutions architect in a big data environment.
Proven track record in owning large-scale data systems and leading cross-functional data initiatives involving data engineering, data science, and analytics teams.
Experience delivering data products for both revenue-generating and platform-scale contexts.
Hands-on experience with large-scale data collection, classification, curation, and delivery systems, especially in companies that build or sell data products.
Experience driving data modeling, transformation, classification and delivering complex entity relationships and high-quality standards.
Practical exposure to AI/ML productization in partnering with data science teams.

Requirements:
At least 2 years experience with SQL/pySpark for data analysis - Must
Experience in Python scripting - Must
Excellent verbal and communication skills in English - Must
AWS Infrastructure experience - Big Advantage
Working with clients - Big Advantage.
Proficiency in Online Marketing/Online Services - Advantage
At least 2 years work experience in Online/Tech Company - Advantage
Team player, autodidact, fast learner with excellent analytical, research and business skills.
Demonstrates initiative and a proactive mindset -Must
Experienced in independently managing complex projects from start to finish.
Have a Bachelor's in Statistics, Computer Science, Engineering, or related field.
Master's degree - Big Advantage.

Requirements:
At least 2 years of work experience in a Tech Company - Must
At least 2 years experience in Python scripting - Must
Experience with SQL for data analysis -Must
Knowledge and understanding of the statistical principles, concepts, methods, and standards- Must
Hadoop/Spark/AWS Infrastructure experience - Big Advantage
Ability to visualize data and experience with a visualization tool and modules (mlplot, matplolib, sns)- Big Advantage
Excellent verbal and communication skills (in English) - Must
Team player, autodidact, fast learner with excellent analytical, research and business skills.

Requirements:
Key Responsibilities: Data Analysis & Insights · Extract, clean, and manipulate data using SQL, Python and AI Tools. · Analyze transaction data to identify trends, anomalies, and opportunities for optimization, supporting business objectives. · Monitor fraud patterns and support risk mitigation strategies using advanced analytics. · Provide insights for settlement processes, banks reconciliation and customer behavior analysis. · Develop and maintain dashboards and reports for payment performance, risk metrics, and operational KPIs to provide clear, actionable insights.
Collaboration & Stakeholder Support · Work closely with the business unit, product, R&D, engineering, data and compliance teams to deliver tailored analytical solutions, improve payment flows and reduce friction. · Communicate findings and insights effectively to both technical and non-technical stakeholders. · Provide data-driven recommendations to support strategic and operational decisions. Data Quality & Optimization · Ensure accuracy, consistency, and reliability of data used in analysis and reporting. · Ensure data integrity and compliance with regulatory standards. · Contribute to continuous improvement of data processes, tools, and methodologies. · Collaborate with data engineering teams to enhance data accessibility and efficiency.
Qualifications: Experience:
* Minimum 2–3 years of professional experience in data analytics, preferably in payments, fintech, or banking.
* Familiarity with payment systems (card networks, acquiring/issuing, digital wallets). - advantage
* Knowledge of chargebacks, and regulatory compliance. - advantage o Understanding ML techniques for risk analytics and exposure to cloud data platforms (Azure, AWS, GCP, DBX) are advantages. Technical Skills:
* Strong proficiency in SQL for querying and manipulating data.
* Working knowledge of Python for data analysis (e.g., Pandas, NumPy, visualization libraries).
* Experience with BI platforms for building dashboards and reports.
* Experience working with AI Tools Soft Skills:
* Strong analytical and problem-solving mindset with attention to details.
* Ability to translate data into business insights.
* Excellent communication skills and ability to collaborate across teams.