[Hiring] Business Analytics Consultant @EPAM

Role Description

Do you enjoy taking a data product from an idea to something people use and rely on? Can you connect an industry challenge with the right architecture, technologies and delivery approach—and stay involved until the solution is working in practice? If you bring hands-on delivery experience and the confidence to work directly with clients, we'd like to meet you. We are looking for a Business Analytics Consultant to join our Data Practice and design, develop and deliver data products for organizations across sectors such as financial services, retail, life sciences and energy.

You may bring deep experience in one industry or have delivered solutions across several. What matters most is your ability to understand how a business works, identify where data can create value and turn that opportunity into a usable product. You will work with stakeholders and delivery teams throughout the product lifecycle:

• From discovery and solution design through development, deployment and adoption.
• Draw on your technical experience to choose approaches that fit the problem, whether they involve AI, cloud platforms, large-scale data processing or other technologies.
• Help clients understand the trade-offs behind those choices and measure the outcomes they achieve.

Responsibilities:

• Lead data product workstreams from discovery and solution design through development, deployment and adoption.
• Work with clients to understand industry-specific processes, challenges and opportunities, and define the business outcomes a data product should achieve.
• Translate business needs into product requirements, technical designs and delivery plans that teams can put into practice.
• Contribute hands-on to the development of data products, applying your technical expertise while working with specialists from other disciplines.
• Evaluate architectures, tools and technologies—including AI, cloud platforms and large-scale data processing where appropriate—and make informed trade-offs based on value, feasibility, performance and cost.
• Guide products from prototype to production, addressing considerations such as data quality, security, reliability, monitoring and maintainability.
• Lead workshops and technical discussions with business and technology stakeholders, explaining solution choices and aligning teams around delivery priorities.
• Measure product performance, adoption and business impact, and use what you learn to improve the solution after launch.

Qualifications

• 7-10+ years of hands-on experience developing and delivering data products or data-intensive software solutions.
• A track record of taking products beyond prototypes into production, including deployment, monitoring and improvement after launch.
• Strong technical expertise in at least one relevant discipline, with the ability to contribute directly to solution design and development.
• Experience designing architectures and making practical trade-offs around scalability, reliability, security, performance and cost.
• Experience working with data across the product lifecycle, from acquisition and processing to making it useful in an application, service or decision-making process.
• Understanding of how technologies such as AI, cloud platforms and large-scale data processing can support data products, and the judgment to choose an approach suited to the problem.
• Experience translating business needs into product requirements and working with others to deliver against them.
• Knowledge of the business processes and metrics in at least one industry, and the ability to apply that knowledge to product decisions.
• Ability to lead discussions with business and technical stakeholders, explain technical trade-offs clearly and guide a workstream through delivery.
• Strong communication skills in English.

Requirements

• Deep experience in a business industry—such as financial services, retail, life sciences, energy or another sector—and a record of delivering data products that address its specific processes and challenges.
• Experience delivering data products across multiple industries and adapting solutions to different business contexts.
• Depth in more than one technical discipline, such as software engineering, analytics, data engineering, machine learning or product architecture.
• Experience modernizing existing data platforms or bringing experimental solutions into production.
• Experience delivering products in regulated environments, where data privacy, security and governance shape technical decisions.
• Experience using product feedback and usage data to improve a solution after launch.
• Experience mentoring engineers or other technical specialists and helping teams adopt effective delivery practices.
• Experience bringing AI-enabled products into everyday use, including integration with existing workflows, user adoption and measuring their impact after launch.