Director of Data Science & and Advanced AI (DSaaS)
- Job Title
- Director of Data Science & and Advanced AI (DSaaS)
- Requirement ID
- Boston, MA 02421
- Other Location
Director of Data Science - Advanced AI (DSaaS)
Location: Boston, MA
Type: Direct Hire
Head of Data Science and Advanced Analytics (DSaaS) is a core position in the Enterprise Data Services (EDS) team responsible for delivering best-in-class data science capabilities as the preferred innovation competency center experts. Our story is one of transformation, leveraging our data assets to make the lives of our patients, HCP, and employees more innovative and actionable. As the Senior Director of Data Science & Analytics, you will play a key role in building a core team and developing advanced capabilities that unlock our company vision to transform digital experiences thru data science techniques reporting directly to the CDO. You will be responsible for advancing data science & advanced analytics capabilities, including defining the proper organization, tools & technology, processes, and governance needed to meet the needs of our business partners as a federated model. This exciting new role is responsible for working across our client on the strategy, use case exploration, and deployment of AI-driven offerings as a Service.
- Design, own, and implement EDS data science strategy in line with the overall business objectives with extensive experience developing and deploying ML/AI-enabled products and services at scale with significant experience in deep learning.
- Build and direct a high-performing data science team, providing leadership, guidance, and mentorship to team members. Leverage ICC and Strategic resource model globally and remotely for niche skills.
- Review architecture and design to deploy predictive models and algorithms that support business decisions.
- Results-driven with a proven track record as a computational pharma/biotech industry leader.
- Establish and maintain relationships with critical stakeholders/data science citizens across the organization to ensure data science initiatives align with business goals, ROI, and successful deployment of algorithms/data products.
- Lead the development of advanced analytical capabilities to create long-term strategic data/analytics assets for the company. Build tools and solutions to measure model performance over time.
- Provide data governance on data science work (sandbox testing, artifacts to ensure the "right way to perform"), ensuring accuracy, security, and AI/ML ops execution excellence.
- Grow and lead a world-class team of skilled bioinformatic and computational data scientists and engineers focused on successfully deploying analytics use cases that drive actionable insight on our big data platform.
- Build out an Advanced analytics community of practice with the charter of knowledge sharing, improving adoption and
- Influence architecture governance, including Architecture Review Board (ARB) and Architecture Innovation Committee (AIC).
- Manage a portfolio of use cases and implementation of Data Science capabilities by providing transparency of projects, registered algorithms (deployed), and innovation lab exploration.
- Collaborating with the EDS practice ensures alignment of critical data science dependencies such as Data Quality, Engineering, Acquisition, and Platform as a Service that enables and elevates AI.
- Responsible for leading the development and deployment of cutting-edge machine learning models, data science tools, & advanced analytics, including incrementality testing & customer analytics, aimed at driving client value across multiple business verticals.
- Foster collaborative innovation with key strategic partners in the bio-pharma sector to support critical projects and capacity demand.
- Master's or Ph.D. in Data Science, Computer Science, Mathematics, Statistics, or a related field. Expertise in Big Data Platform Architecture and enterprise data capabilities.
- Bachelor's degree in a relevant field; or relevant work experience.
- At least 10 years of experience in data science, with a proven track record of success in leading and managing a large cross-functional team.
- Strong knowledge of Data Science such as Business Intelligence, Artificial Intelligence, Machine Learning, Advanced Analytics, Big Data, Data Management, and Data Governance.
- Demonstrated leadership and project management skills in deploying, leading, and implementing successful projects.
- Strong leadership skills, with the ability to inspire and motivate a team to achieve ambitious goals.
- Expertise in architecting, designing, and deploying predictive models and algorithms in real-world business environments.
- Strong experience in AWS Data Services (Redshift, Elasticsearch, S3, API Gateway, Lambda, GlobalSCAPE) and third-party tools such as Informatica, Collibra, MuleSoft, Databricks, PowerBI, and Tableau.
- Strong technical and in-depth knowledge of data mining, machine learning, statistical modeling, and programming languages like Python or R.
- Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and present complex data-driven insights to non-technical stakeholders.
- Excellent stakeholder management skills.
- Ability to adjust priorities quickly as circumstances dictate.
- Experience in data models and data architectures; able to develop logical and physical data models and understand slowly changing dimension patterns.
- In-depth business acumen and pharmaceutical or life sciences industries functional/technical knowledge; flexible analytic approach and proficiency in one or more scripting languages, such as Python or R.
- Familiarity with information management practices, regulatory requirements, and data privacy laws, especially those uniquely affecting the pharmaceutical industry.
- Knowledge of business ecosystems, SaaS, infrastructure as a service (IaaS), platform as a service (PaaS), SOA, APIs, open data, microservices, relational and non-relational databases systems such as SQL, Redshift, PostgreSQL, or Vertica. Familiar with modern machine learning techniques for classification and regression and knowledge of A/B testing, experimental design, and general statistical modeling.
- Ability to define and communicate compelling, business-enabling technology vision and the business value of this vision, along with actionable roadmaps to achieve target state architecture across people, process, and technology dimensions.
- Demonstrated proficiency in leading a data science department in developing new insights, advanced modeling techniques, and data science capabilities.
- Initiate data science programs across the company to improve departmental performance, focus on revenue growth, and achieve the business' overall targets and objectives.
- Takes the initiative and stays current with the latest data science trends, techniques, and best practices, determining how to incorporate the most suitable methods in the department.
- Exposure to agile working methods, such as Scrum / SAFe and DevOps methodologies.
Strictly No 3rd Party Vendors
Strictly No 3rd Party Candidates
- Required Skills
Big Data Platform Architecture
AWS Data Services (Redshift, Elasticsearch, S3, API Gateway, Lambda, GlobalSCAPE)
Informatica, Collibra, MuleSoft, Databricks, PowerBI, and Tableau
Data mining, machine learning, statistical modeling, Python, or R.