Job Responsibilities:

As Manager-Data Science, 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 up-to-date development tools and writing code collaboratively.
- Intermediate knowledge of Cloud technologies and experience in developing data science solutions in one or more cloud platforms.

Pharma & RWE skillset:

- 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.

📌 Data Science Manager (Bengaluru)
🏢 MathCo
📍 Bengaluru