דרושים » תוכנה » Mid-Level Game Economy Manager

We are looking for a Game Economy Manager to join our team. In this role, you will be responsible for designing and controlling the game economy systems for one of our top-grossing mobile games.
Responsibilities:
Work closely with product & monetization teams to design and implement new game content, features, and live ops
Model and balance complex systems in the game, to maintain a healthy and growing game economy
Monitor, tune, and price the game features and in-app purchases for driving player engagement and optimizing different KPIs
Balance customer experience and revenue opportunity for in-game currency and virtual goods.
Perform data analysis, A/B testing, and advanced modelling for game systems and player experiences.

We are looking for an experienced Data Analyst to lead the analysis dept. in a growing gaming company, analyzing game and monetization related data, delivering insights to different company departments and helping us grow and enhance our game's performance
Responsibilities:
Analyze large, complex data sets representing users behavior and performance, inform, influence and support data driven business decisions regarding marketing, product, economy and monitization.
Provide actionable recommendations and conclusions from game data to shape features, game economies and future product road-maps
Balance and monitor essential flows in the game
Build and maintain dashboards and reports to follow and monitor game KPIs
Strive for never ending data driven optimization and excelency

What will you do?
Design the user experience from an economic point of view, trying to predict the players' behavior according to the data we already have.
Price the game's virtual currencies.
Build simulations and predictive models to forecast the results of changes to the content proactively.
Work with product teams on balancing new features.
Monitor individual and macro player balances to ensure the overall health of the game's economy.
Analyze large, complex data sets to address strategic and operational business decisions.

Opportunity to work on high-scale gaming projects with a passionate and talented team.
A culture of innovation, collaboration, and continuous learning.

What you'll be doing:
Identify key business questions and define corresponding data events and metrics to ensure actionable insights.
Deep dive analysis in various game aspects, including economy, monetization, and gameplay, to identify opportunities for optimization and enhanced player engagement.
Conduct overall business reviews to monitor User Acquisition (UA) performance and key profitability KPIs, ensuring alignment with company objectives and growth targets.

Our Strategy & BI department is looking for a talented, business-oriented, and driven Senior Business Analyst to join the team.
This person will play a key role in the analysis and optimization of the rapidly expanding business activity and will take part in the execution of growth strategic initiatives.
The ideal candidate is an energetic team player with exceptional data analysis skills, who can use data to effectively drive results in a fast-growing company and aims to enter the business world. A self-motivated with a high degree of comfort and the ability to leverage data to drive decision-making and turn action items into enhanced performance
Responsibilities:
Analyse and optimize products and activities and use data-driven conclusions to influence and support tactical and strategic decisions.
Build and maintain reports, dashboards, and metrics.
Collaborate with stakeholders from various departments to carry out plans and translate strategy into business results.
Conduct customer analysis including segmentation, profitability, customer value, trends, and behavior.
Work with large amounts of data and build tools to streamline processes.
Conduct ad-hoc analysis under tight deadlines.

We are looking for a Market Data Analyst.
Responsibilities:
Detect anomalies and automatically perform the appropriate remediation action, improving data quality, consistency and reliability.
Perform analyses on large quantities of data to identify trends and automate the recalibration of the model parameters that generates our implied data (volatility surfaces, implied dividends, correlations, projected dividends, securities lending).
Utilize in depth understanding of the Equity Derivatives market and technical skills to provide detailed analysis to clients on their pricing of complex structured products and portfolio valuation.
Design, develop, and implement automated monitoring, and dynamic thresholds.
Initiate projects, write specs, interact with R&D, Quants, Dev and Q&A until final push to production.
Be part of the creation and maintenance of data pipelines and ETL processes to ensure data quality and availability.
Leverage programming skills and financial market experience to clean large data sets of historical implied data.
Keep up with the industry trends and innovation in the Equity Derivatives industry and data quality domain.
Collaborate closely with Product team and give feedback on clients challenges to identify opportunities and deliver value-added solutions to enhance our clients business.
Excellent written and verbal communication skills to escalate bugs or clients requirements to Quants and explain technical processes and solutions to Business Partners and Sales.

We are looking for a Data Scientist- Autonomous.
The Research and Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more).
As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

We are seeking a talented BI Developer to join our team. The ideal candidate will have a strong background in business intelligence, data analysis, and database management, with a passion for gaming. The BI Developer will play a key role in designing, developing, and maintaining our data infrastructure, as well as providing insights and analytics to support data-driven decision-making across the organization.
Responsibilities:
Design, develop, and maintain data pipelines and ETL processes to extract, transform, and load data from various sources into our data warehouse.
Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
Develop and maintain dashboards, reports, and visualizations to provide insights into key business metrics and performance indicators.
Perform data analysis to identify trends, patterns, and opportunities for optimization and improvement.
Optimize and tune SQL queries and database performance to ensure efficient and reliable access to data.
Collaborate with data engineers and other stakeholders to continuously improve data quality, accuracy, and reliability.
Stay up-to-date with industry trends and best practices in business intelligence, data analytics, and gaming technology.

We are looking for a Senior Data Scientist.
The Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing:
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

We are looking for a Data Scientist.
The Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing:
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities