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Sr. Director, Data Generation

Medical Affairs | Waltham, MA | Full Time

Job Description

About Oncopeptides:

Oncopeptides is a pharmaceutical company focused on the development of targeted therapies

for difficult-to-treat hematological cancers. The company is focusing on the development of the

lead product candidate melflufen, a novel peptide-drug conjugate that rapidly delivers a cytotoxic payload into tumor cells.  Melflufen is in development as a new treatment for the hematological cancer multiple myeloma and is currently being tested in multiple clinical studies including the pivotal phase 2 HORIZON study and the ongoing phase 3 OCEAN study. Oncopeptides’ US headquarters is based in Waltham, MA with an office in Mountain View, CA/Bay Area, and global headquarters is in Stockholm, Sweden. The company is listed in the Mid Cap segment on Nasdaq Stockholm with the ticker ONCO.

The company is in a strong financial position and has an effective Executive Team and Board of Directors. Discover more about Oncopeptides at


The Senior Director Data Generation reports to the US Head of Medical Affairs and is responsible for providing analytical expertise and insight in preparation of and post commercial launch. This role is intended to make significant contributions in maturing process efficiency, defining and delivering on  data analysis, methods of inquiry, life-cycle and tools for understanding data. The Senior Director will guide strategic and operational projects. The Senior Director of  Data Generation must be comfortable sorting through competing priorities, project execution, mentoring of senior and junior staff, matrix structures, multi-country responsibility, and the stand up of new enterprise capabilities to better achieve analytic outcomes. The role will be highly visible, and therefore is expected to positively impact the overall execution of data science, data projects and delivery of analytical insight.

This position is based in Waltham, MA

Essential Duties and Responsibilities:

  • Through assessment of intangible variables, identifies and evaluates fundamental issues, providing strategy and direction for major functional areas. 

  • Develop a deep understanding of internal stakeholders' data and analytical needs. 

  • Data acquisition and analysis to inform commercial strategies, tactics and decisions. 

  • Coordinate the procurement of various datasets, design and implement analytical solutions in support of various commercial initiatives e.g. understanding of current market landscape based on RWD sources, opportunity identification, customer targeting, ROI analytics etc.

  • Demonstrate a thorough understanding of RWD sources (EMR, claims, clinical, etc.) to guide the organization on appropriate data sources to use for addressing key business questions. 

  • Lead the design and delivery of advanced quantitative data analyses leveraging large/complex datasets. 

  • Champion the use of local customer insight in strategic and resourcing decisions across the business. 

  • Build advanced analytics capabilities. Test and deploy new analytical capabilities for the business. 

  • Monitor the external environment to stay up to date on leading analytic capabilities, both within and outside of pharma, which can be applied within the organization. 

  • Collaborate closely with the Business Insights team to ensure insights from secondary data are appropriately integrated with insights from other sources. 

  •  Collaborate with various other groups including Marketing, Access, Sales and other stakeholders. 

  • Contractor/ vendor management, as needed. 

Experience, Education, Training, Traits:

  • Masters degree in Science, Bioinformatics, Computational Biology, Information Technology or related formal informatics training in healthcare/life sciences.

  • 15 +  years professional experience with demonstrated achievements in a senior level position.

  • Exceptional seasoned management, project management and operational management experience.

  • Demonstrated experience in growing and mentoring a  team.

  • Expertise in algorithmic implementation, pipeline, data handling, and multi-mode data manipulation.

  • Familiar with specialized commercial platforms and open source apps, database, visualization, data integration and analysis tools for high dimensional data.

  • Experience working with large complex data and corresponding query/ programming languages such as SAS, R, Python, or SQL plus experience with other big data technology such as Hadoop. 

  • Proficiency in manipulating and extracting insights from large longitudinal data sources, such as Claims, EMR and other patient level data sets.

  • Familiar with cancer genomic data sources.

  • Ability to build and foster solid relationships cross-functionally - a team player.

  • Excellent verbal and written communication skills; the ability to interface effectively with scientists, manufacturing and clinical staff to communicate / discuss results and ideas.

  • Prior experience in biotechnology and/or pharmaceuticals industry.

  • At ease working in a fast paced highly ambiguous complex environment.

  • Able to tell a story with the data to communicate complex ideas.

  • Demonstrated experience handling high fidelity data for regulatory submissions.

  • Deep understanding of experimental and analytical methodologies used in the biological space (NGS, RNA-Seq, etc.).

  • Predictive modelling, artificial intelligence, data science.

  • Strong creative thinking and problem-solving skills.

  • Strong in bioinformatic life-cycle from initial data source plan, through data cleaning and analysis to visualization and report out.

  • Ability to lead develop customized tools where commercial platforms do not exist

  • Hands-on experience in the fields of bioinformatics including working with bioinformatics tools (e.g., BLAST, GATK, Cell Ranger, samtools, VEP), statistical environments (e.g., R, S+, Matlab) and various public and proprietary data repositories (e.g., TCGA, GTEx, dbGaP, Ensembl, UCSC genome browser,Array Studio).

  • Experience with manipulation, interpretation, and innovative analysis (e.g. novel algorithm development) of large biological datasets.

  • Familiar with best practices, system development life cycle management, infrastructure and operations.

  • Cloud computing systems (e.g. Amazon Web Services).

  • Understanding of meta models, taxonomies and ontologies, as well as of the challenges of applying structured techniques (data modelling) to less-structured sources.

  • Familiarity with master data, business intelligence, data lake, and data warehouse techniques.

  • Excellent oral and written communication skills; including describing complex data topics in simple terms. 

  • Considerable experience with presentation of statistical analysis results to a non-technical audience. 

  • Strong organizational skills and time management; ability to manage diverse range of simultaneous projects.