Data Scientist - Real-Time Pricing & Optimization
Posted 2 days 14 hours ago by Freelanceshop
Startup Inno is seeking a highly analytical and innovative Data Scientist - Real-Time Pricing & Optimization to join our fast-growing data and product intelligence team. In this role, you will design, build, and deploy advanced machine learning models that power dynamic pricing strategies and real-time optimization systems across our digital platforms. You will work closely with product managers, engineers, and business stakeholders to transform large-scale data into actionable insights that directly impact revenue, customer experience, and market competitiveness.
This is an exciting opportunity for a data-driven professional who thrives in a high-growth, agile startup environment and wants to work on real-world problems involving streaming data, algorithmic decision-making, and large-scale optimization.
Key ResponsibilitiesDevelop and implement real-time pricing models using machine learning, statistical modeling, and optimization techniques.
Design end-to-end data pipelines for ingesting, processing, and analyzing large volumes of structured and unstructured data.
Build predictive and prescriptive models to optimize pricing, promotions, demand forecasting, and revenue management.
Collaborate with software engineers to deploy models into production environments and ensure real-time performance.
Conduct A/B testing and experimentation to evaluate pricing strategies and model effectiveness.
Monitor model performance, retrain models, and continuously improve algorithms based on business feedback.
Translate complex analytical results into clear insights and recommendations for non-technical stakeholders.
Stay updated with the latest developments in data science, machine learning, and optimization techniques.
Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
Strong proficiency in Python or R for data analysis and model development.
Experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, or similar.
Solid understanding of statistical modeling, regression, classification, and time-series analysis.
Experience working with SQL and NoSQL databases.
Familiarity with big data tools and platforms (Spark, Hadoop, Kafka, etc.).
Knowledge of real-time systems, APIs, and model deployment pipelines.
Strong problem-solving skills with a business-oriented mindset.
2-5 years of professional experience in data science, machine learning, or advanced analytics roles.
Proven experience in pricing analytics, revenue optimization, demand forecasting, or similar domains is highly preferred.
Experience working in a startup or fast-paced technology environment is an advantage.
Demonstrated track record of building and deploying data-driven models in production.
Full-time position (40 hours per week).
Flexible working hours with a hybrid or remote-first approach, depending on location and team needs.
Occasional overlap with global teams may be required for collaboration and project alignment.
Strong analytical thinking and quantitative reasoning skills.
Ability to work independently and manage multiple projects simultaneously.
Excellent communication skills, with the ability to explain complex concepts in simple terms.
Strong business acumen and understanding of how data drives strategic decisions.
High level of curiosity, creativity, and passion for solving complex problems.
Adaptability and willingness to learn new tools, technologies, and methodologies.
Competitive salary and performance-based incentives.
Flexible working arrangements (remote/hybrid options).
Health and wellness benefits package.
Continuous learning and professional development opportunities.
Access to cutting-edge tools, technologies, and real-world datasets.
A collaborative, inclusive, and innovation-driven work culture.