Assistant Manager - Solution Owner
India - Chennai
AstraZeneca
AstraZeneca is a global, science-led biopharmaceutical business and our innovative medicines are used by millions of patients worldwide.Job Title - Assistant Manager - Solution Owner
Career Level - D2
This role will be responsible for overseeing the development, implementation, and optimization of solutions within the Commercial Organization, driving strategic and operational/business excellence. This role holds accountability for service delivery with quality and agility and requires considerable hands-on technical expertise and proactive leadership in solution management. The Solution Owner will support and design end-to-end solutions that enable data-driven decisions based on rigorous analysis and the best available information. A high level of proficiency in solution architecture, system integration, and project management is required. This role primarily works closely with Brand Analytics GIBEX partners (also in few cases with Marketing, Medical, Market Access, Sales, Forecasting, and other Commercial Operations business partners) based on the business requirements/needs. In addition to strong technical skills, the Solution Owner should have excellent communication skills with a demonstrated track record of effective business partnership, as evidenced by material business impact and influencing capabilities. The candidate will also be required to continuously evaluate new technologies and methodologies to enhance solution delivery overall.
- Deep Customer Understanding and Solution Delivery: Deep understanding of internal customers' technological and solution needs, focusing on delivering integrated and innovative solutions.
- Technological Innovation and Adoption: Champion the use of advanced technologies and methodologies in leading the development, deployment, and embedding of new capabilities.
- Data Governance and Analytics: Collaborate with data governance teams to ensure data integrity, security, and privacy. Should have working knowledge with GitHub and Data Products/Repositories. Utilize predictive analytics and machine learning models to provide actionable insights and recommendations for business decisions.
- Cloud Adoption and Business Outcomes: Drive the adoption of cloud-based solutions to enhance scalability and flexibility of analytics capabilities. Ensure business outcomes and objectives are accomplished within approved time frames, scope, and budget.
- Project Governance and Execution: Foster strong project governance and execution assurance processes. Handle the delivery of projects with multiple partners and technical, business, and data components.
- Continuous Improvement and Learning: Instill a culture of continuous improvement, testing, and deployment of new capabilities. Access appropriate information, summarize findings, and apply deeper technical skills to optimize solutions.
- Cross-Functional Collaboration and Mentorship: Coordinate and mentor/coach cross-functional teams to ensure seamless integration of solutions. Collaborate with global and local teams, functions, and service partners on cross-functional initiatives.
- Stakeholder Management and Solution Documentation: Manage stakeholder relationships/expectation to ensure high-quality, cost-effective solutions. Develop/maintain comprehensive documentation for all solutions, ensuring transparency and easy knowledge transfer.
- Training and Compliance: Conduct regular training sessions for team members. Ensure compliance with regulatory requirements and industry standards in all solution implementations.
- Issue Resolution and Risk Management: Establish processes to identify and resolve complex project issues. Ensure contingency plans are identified and implemented. Build metrics and manage with a higher level of information.
Job Description:
Essential for the role:
- Education and Experience: Bachelor's degree in a quantitative field and 7+ years of experience in data modeling, warehousing, architecture, integration, project management, or advanced analytics, preferably in life sciences/healthcare business.
- Technical Skills: Proficiency with tools and technologies such as Python, R, MS Office, SQL, PySpark, and big data platforms like Hadoop/Spark or cloud platforms (AWS, Azure, GCP) and data management tools. Expertise in relational data modelling, with SQL and big data architecture sections, along with strong understanding of data science methodologies/ML algorithms and statistical modeling.
- Business domain: Experience with leading technological platforms and datasets such as IQVIA, Komodo, and transforming/extracting insights from large longitudinal data sources, such as Claims, EMR and other patient level data sets.
- Data Architecture and Engineering: Experience in designing/overseeing the development of data architectures, pipelines, and infrastructure, along with data governance, security, and compliance. Experience in designing and implementing data architectures and pipelines.
- Business Acumen and Collaboration: Collaborate with business leaders to translate strategic goals into data-driven initiatives. Excellent communication and interpersonal skills to work effectively with diverse teams. Proven track record in delivering successful data-driven projects.
- Data Visualization and Insights: Basic to intermediate knowledge of data visualization tools such as Power BI and MSTR, and ability to create data visualizations and dashboards to communicate insights effectively.
- Strategic Thinking and Leadership: Should be able to connect the dots with a broader view to align projects and different POCs/ideas, along with strong mentorship and interpersonal skills to build credibility with leadership teams. Closely works with the people managers and technical leads to provide seamless support to the business.
- Problem-Solving and Critical Thinking: Analytical and proactive mindset to problem-solve, with the ability to engage, build, solve open-ended questions and maintain credibility with Commercial Leadership Team.
- Risk and Time Management: Ability to identify risks and implement mitigation strategies. Strong organization and time management skills.
- Certifications: Certified professional in Analytics, AI/ML, with solution expertise and insight generation in pharma/healthcare such as IQVIA, Komodo, etc.
- Consultative Skills: Should have good experience in consulting terms.
- Brand Knowledge: Knowledge of AZ brand and science is required to deliver e2e solutions especially in understanding business context behind every request.
Desirables:
- An advanced degree into Masters, MBA, or PhD.
- Advanced Analytics and Statistical Modeling: Experience in applying advanced methods like statistical analysis, time series, regression, econometrics, data mining, predictive modeling, and machine learning can be an added value.
- Project Management: Having good experience in project management areas. The ability to see a project through from start to finish and deliver on time.
- Experience working with globally distributed pharma/healthcare datasets.
- Collaborate with data scientists to develop and evaluate machine learning models.
Strong expertise in building e2e reporting and analytical frameworks and solutions for pharma/healthcare
Date Posted
20-Nov-2024Closing Date
30-Dec-2024AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Azure Big Data Consulting Data governance Data management Data Mining Data visualization Econometrics Engineering GCP GitHub Hadoop Machine Learning ML models Pharma PhD Pipelines Power BI Predictive modeling Privacy PySpark Python R Security Spark SQL Statistical modeling Statistics Testing
Perks/benefits: Career development Health care Transparency
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