Job Description
Python SQL Machine Learning Survival Analysis Pharma - Consulting Delivery Management Leadership
Job Responsibilities:
As Manager-Delivery, you will be responsible for a wide range of engagements listed below:
- Collaborate with the Engagement Manager, Account Delivery Manager, and client stakeholders to gather business requirements for the project.
- Develop a comprehensive project plan that aligns with the scope and objectives of the project.
- Develop appropriate solution design that will help client achieve their goals.
- Assign delivery team members to different activities suited to their individual skills.
- Lead the execution of project activities according to the project plan.
- Monitor the project, track milestones, and adhere to agreed-upon timelines and scope.
- Accountable for the delivery quality of the project in question.
- Comply with all the critical dimensions of the delivery scorecard, report as-is facts on those dimensions, and develop and execute action plans to improve delivery scores.
- Lead internal scrum meetings and stand-ups with the clients and Weekly Business Reviews with the clients.
- Ensure compliance with best practices and established processes for quality assurance—for example, using quality assurance checklists, coding best practices, peer reviews, and documentation.
- Provide both business and technical guidance to the delivery team.
- Coach individuals in the team and build a high-performance workplace.
- Establish an environment of mutual trust and respect and encourage the team to experiment with new delivery ideas.
- Review the team's deliverables before sharing them with clients, including codes, presentations, worksheets, emails, etc.
Required Skills (Must have):
Tech:
- Advanced programming knowledge in Python and SQL.
- Advanced knowledge in Probability and Statistics, including hypothesis testing.
- Advanced knowledge in Practical Machine Learning and awareness of the key-pitfalls in the practice of machine learning and approaches to addressing them.
- Knowledge of data visualization technologies like Tableau, and PowerBI, and comfortable using relevant libraries in Python like seaborn and matplotlib.
- Experienced in modern development tools and writing code collaboratively.
- Intermediate knowledge of Cloud technologies and experience in developing data science solutions in one or more cloud platforms.
- Experience working with patient level data such as hands‑on experience with RWE datasets such as - Optum, Komodo, IQVIA Claims in depth
- Experience working on Real World Evidence Use cases such as patient journey, Identifying Adherence, Drop‑offs, Productivity and Days on therapy and Survival analysis Sequence model for
- Ability to understand and solution for Pharmaceutical and Lifesciences analytical and business solutions
Non Tech:
- Ability to recognize and pursue pragmatic alternatives vis‑à‑vis a perfect solution, balancing priorities of time with potential business impact.
- Plan projects, break them down across individual data scientists in the team, track their performance and manage risk.
- Ability to storyboard an entire presentation to a non‑technical audience.
- Ability to work independently to develop data science solutions, while also being able to work as part of a team to communicate findings and collaborate on solutions.
- Strong written skills. This is required for submitting technical papers, whitepapers, and developing project documentations.
- Technical leadership and mentorship to the community of data scientists in the organization.
Required Skills (Good to have):
Tech:
- Advanced knowledge in one or more areas besides Machine Learning –Operations Research, Natural Language Processing, Deep learning and its applications, Time Series forecasting at scale, Reinforcement Learning, Graph Machine Learning, Explainable Machine learning.
- Advanced understanding of Cloud technologies and experience of deploying applications on cloud.
- Advanced knowledge of project management methodologies and tools
- Advanced knowledge levels in SQL and Python
- Intermediate to advanced knowledge in other areas of data science—namely, technical areas such as time series forecasting, Bayesian data analysis, Operations Research, and analytics domain areas such as Pricing analytics, Media Mix Modeling, B2B/B2C Customer analytics, etc.
Non Tech:
- Hands‑on experience working in the EMEA/Asia Pacific healthcare
- Ability to solution critical business problems into its component parts and match each such part with an appropriate technical approach.
- Solution proposals, collaborating with growth, customer success, and central solutioning functions.
Being a Mathemagician:
- Understand & embody MathCo’s culture and way of working.
- Demonstrate an ownership mindset to drive results, striving for excellence.
- Engage actively and contribute to initiatives fostering company growth.
- Support diversity and understand different perspectives.
Preferred Educational Qualifications:
- An undergraduate degree in engineering, statistics, mathematics, computer science, or another technical field.
- For those with an undergraduate degree in non-technical fields, relevant prior work experience and technical aptitude will be important.
As a testament to our growth, we have been:
- Positioned as a Leader in Top Generative AI Service Providers – PeMa
- Quadrant 2023 by AIMResearch
- Recognized among the Inspiring Workplaces in North America, 2023
- Accredited for Inclusive Practices by Great Place to Work Institute, India
- Recognized among India’s Best Workplaces™ for Diversity, Equity, Inclusion Belonging 2023 by Great Place To Work® India