Senior Data Consultant - Media and Data Solutions Development Department (MDSD)

Job Description:

Department Overview

Media and Data Solutions Development Department (MDSD) deliver superior User Experience via innovative and stable Internet Media products and build Data Solutions on the acquired Data for internal and external clients. MDSD supports a variety of products, such as Super Point Screen, Rakuten Web Search, Rakuten Kakeibo, Rakuten Insight. Our core competencies are industry-leading technical expertise and technical solution design capabilities.

Position:

Why We Hire

In todayʼs fast-paced, data-driven world, software product development teams must fully leverage data to make informed decisions and create innovative products. Media and Data Solutions Development Department (MDSD) is committed to building cutting-edge internet media and data service products that are powered by data insights. To achieve this, we are seeking a highly skilled and experienced Senior Data Consultant to bridge the gap between business needs, performance and technical development. This role is critical to enable informed decision-making, prioritization, and resource allocation across our software product portfolio. Additionally, the Senior Data Consultant will play a key role in promoting Digital Transformation (DX) by leveraging advanced analytics, machine learning (ML), and large language models (LLMs) to maximize development productivity and unlock new opportunities for innovation. The Senior Data Consultant will lead and collaborate with data analysts, data engineers, and data scientists, ensuring that the teamʼs collective expertise is harnessed to deliver impactful, data-driven solutions.
If you are passionate about data, have a proven track record of delivering actionable insights, and thrive in a collaborative and diverse environment, please join us and help us shape the future of our media and data solution products.

Position Details

Key Responsibilities

Data-Driven Product Portfolio Management

- Design and implement a data-driven framework for software product portfolio management, enabling the organization to make informed decisions about product prioritization, resource allocation, and performance tracking.

- Collaborate with product managers and business stakeholders to define and monitor structured Key Goal Indicators (KGIs) and Key Performance Indicators (KPIs) for the product portfolio.

- Provide actionable insights and recommendations to optimize the product portfolio, ensuring alignment with business objectives and market trends.

- Develop dashboards and reporting tools to provide real-time visibility into the performance of the product portfolio.

Consultation for Data-Driven Operation Setup

- Act as the primary point of contact between the data team and business stakeholders, ensuring seamless communication and alignment on priorities.

- Act as a strategic partner to business stakeholders, organizing discussions to clarify business objectives and define measurable outcomes (KGIs and KPIs).

- Translate high-level business goals into actionable data strategies and analytics roadmaps.

- Provide expert guidance to business and development teams on how to leverage data to achieve their objectives, ensuring alignment between business needs and technical solutions.

Ownership and Collaboration

- Lead and collaborate with a team of data analysts, data engineers, and data scientists, ensuring alignment on project goals and deliverables.

- Provide mentorship and guidance to team members, helping them grow their technical and professional skills.

Promotion of Digital Transformation (DX) with Machine Learning and LLMs

- Drive operational transformation by designing and implementing machine learning (ML) models and solutions to automate processes, improve decision-making, and enhance operational efficiency.

- Leverage large language models (LLMs) to develop innovative solutions, such as intelligent chatbots, automated content generation, and natural language processing (NLP) applications, to improve customer experiences and streamline internal operations.

- Identify opportunities to integrate ML and LLM technologies into the product portfolio to create competitive advantages and new revenue streams.

Mandatory Qualifications:

Education

- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
 

Experience

- 5+ years of experience in data consulting, data analytics, or data science roles, preferably in large business or IT consulting environments.

- Proven experience working with cross-functional teams, including business stakeholders, product managers, and software engineers.

- Demonstrated ability to facilitate discussions with business teams to define and refine KGIs and KPIs, ensuring alignment with organizational goals.

- Project experience in designing and implementing machine learning models and solutions for real-world business problems.

- Experience working with large language models (LLMs) and Machine Learning powered solutions.

- Proven track record of delivering data-driven solutions that have a measurable impact on business outcomes, particularly in the context of product portfolio management.

Technical Skills

- Expertise in data analysis, data modeling, and data visualization tools (e.g., SQL, Python, R, DOMO, Tableau, Power BI).

- Strong knowledge of data engineering concepts, including ETL pipelines, data warehousing, and cloud platforms (e.g., AWS, Azure, Google Cloud).

- Proficiency and/or crips understanding in machine learning techniques and frameworks (e.g., TensorFlow, Scikit-learn, PyTorch).

- Experience with LLMs and NLP tools such as OpenAI GPT, Hugging Face Transformers, or similar frameworks.

- Solid understanding of database systems (e.g., relational, NoSQL) and big data technologies (e.g., Hadoop, Spark).

Leadership and Communication Skills

- Exceptional ability to lead and collaborate with a multidisciplinary team of data analysts, data engineers, and data scientists.

- Strong interpersonal and communication skills, with the ability to convey complex technical concepts to non-technical audiences.

- Proven track record of building trust and credibility with stakeholders at all levels of the organization.
- Fluency in both Japanese and English.

Desired Qualifications:

- Advanced degree (Master degree in Computer Science or MBA) in a relevant field.

- Experience in the development of internet service products or SaaS platforms.

- Familiarity with Agile methodologies and product development lifecycles.

- Knowledge of advanced analytics techniques, such as reinforcement learning, deep learning, or generative AI.

- Experience with data privacy regulations and compliance (e.g., GDPR, CCPA).

- Certifications in relevant technologies or methodologies (e.g., AWS Certified Data Analytics, Microsoft Certified: Azure Data Scientist, Certified Analytics Professional).

- A strong network within the data science and analytics community.

Other Information:

Additional information on Location

Tokyo

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