Data Analyst Job at Fidel Consulting KK, 東京都

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  • Fidel Consulting KK
  • 東京都

Job Description

Appealing Points:
  • Cutting-Edge Work in Life Sciences: Engage with high-impact projects involving real-world clinical and genomics data, contributing to meaningful discoveries in biotechnology, pharma, and healthcare.
  • Advanced Technical Environment: Utilize modern data technologies including SQL, ETL pipelines, and cloud platforms, allowing you to work at the forefront of data engineering and life science analytics.
  • Professional Growth & Collaboration: Collaborate with interdisciplinary experts and receive opportunities to document, train, and mentor—enhancing both your technical skills and leadership capabilities.

Annual salary: 6 million and above

Job Responsibilities

  • Data Collection and Integration: Gather, interpret, and integrate complex datasets from multiple life sciences sources, including clinical trial data, laboratory information management systems (LIMS), electronic health records (EHR), genomics, and market research data.
  • ETL Development: Design, develop, and maintain robust ETL (Extract, Transform, Load) pipelines to ensure accurate, timely, and secure movement and transformation of data across platforms and systems.
  • SQL Data Manipulation: Write, optimize, and troubleshoot advanced SQL queries to extract, aggregate, and analyze large volumes of biological, patient, or experimental data.
  • Data Quality Assurance: Conduct rigorous data quality assessments, validate data integrity, and implement quality control measures to ensure reliability and accuracy of analytical results.
  • Domain-Specific Analysis: Perform in-depth analyses relevant to the life sciences sector, such as biomarker identification, clinical outcome analytics, patient cohort segmentation, and real-world evidence studies.
  • Documentation and Training: Maintain comprehensive documentation of analysis methodologies, ETL processes, and standard operating procedures. Provide training or guidance to junior team members as needed.

Job Qualification:

  • Bachelor’s or Master’s degree in Life Sciences, Bioinformatics, Biotechnology, Computer Science, Statistics, Mathematics, or a related field.
  • Demonstrated experience (3+ years preferred) as a Data Analyst in a life sciences, healthcare, or pharmaceutical environment.
  • Expertise in SQL, including advanced querying, database design, and performance tuning.
  • Hands-on experience with ETL tools and practices ( Informatica and custom ETL scripts).
  • Solid understanding of data structures, relational databases, and data warehousing concepts.
  • Strong problem-solving skills and analytical thinking, with the ability to interpret and contextualize data within the life science domain.
  • Excellent written and verbal communication skills, with the ability to convey technical information to non-technical audiences.

Preferred Qualifications

  • Advanced degree (Ph.D., MS) in a Life Science or Data Analytics field.
  • Experience working with clinical data, omics datasets (genomics, proteomics, metabolomics), or pharmaceutical R&D data.
  • Experience with cloud data platforms

Language Skills : Fluent level Japanese (JLPT N1) and Business level English

Holidays & Benefits

Insurances

Commuting allowance

Business trip allowance

Sports facilities and recreation facilities

Educational training / Overseas training system (OJT)

Group life insurance

Casual clothes allowed (office casual)

Company Description 

One of the world's leading professional services companies, transforming clients' business, operating and technology models for the digital era. 

Their unique industry-based, consultative approach helps clients envision, build and run more innovative and efficient businesses. 

Headquartered in the U.S., this company is one of the Fortune 500 companies and is consistently listed among the most admired companies in the world.

[Passive smoking measures]

Indoor smoking

Designated smoking area

Job Requirements: English 2, Japanese JLPT N1, life sciences, healthcare, SQL, etl tools, life sciences sources

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