<div><strong style="color: rgba(0, 0, 0, 0.6);">ProcDNA </strong><span style="color: rgba(0, 0, 0, 0.6);">is a global consulting firm. We fuse design thinking with cutting-edge tech to create game-changing </span><strong style="color: rgba(0, 0, 0, 0.6);">Commercial Analytics and Technology solutions </strong><span style="color: rgba(0, 0, 0, 0.6);">for our clients. We're a passionate team of </span><strong style="color: rgba(0, 0, 0, 0.6);">277+ across 7 offices</strong><span style="color: rgba(0, 0, 0, 0.6);">, all growing and learning together since our launch during the pandemic. Here, you won't be stuck in a cubicle -you'll be out in the open water, shaping the future with brilliant minds. At ProcDNA, innovation isn't just encouraged, it's ingrained in our DNA.</span></div>

ProcDNA Analytics Pvt Ltd

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<p class="MsoNormal"><b>Job Overview</b></p>
<p class="MsoNormal">As a Data Scientist, you will play a key role in delivering end-to-end data science solutions across pharmaceutical and healthcare engagements. The role demands a blend of technical depth, business acumen, and scientific curiosity. You will translate complex business problems into analytical frameworks, develop scalable machine learning and statistical solutions, and generate actionable insights that drive commercial, clinical, and operational impact for clients and patients worldwide. Beyond technical execution, you are expected to think strategically, framing business challenges, designing analytical approaches, and guiding clients toward the most effective data-driven decisions.</p>
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<p class="MsoNormal"><b>Key Responsibilities</b></p>
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<li class="MsoNormal" style="mso-list: l3 level1 lfo1; tab-stops: list .5in;">Own day-to-day execution of data science projects from problem definition to deployment, ensuring methodological rigor, business relevance, and timely delivery</li>
<li class="MsoNormal" style="mso-list: l3 level1 lfo1; tab-stops: list .5in;">Build, tune, and validate advanced machine learning and statistical models, including supervised techniques (classification, regression, uplift), unsupervised methods (clustering, PCA, GMM), transformer models, and analytical frameworks (hypothesis testing, causal inference, survival analysis) using industry-standard libraries</li>
<li class="MsoNormal" style="mso-list: l3 level1 lfo1; tab-stops: list .5in;">Develop clean, modular, and production-ready code with reusable components, adhering to best practices in version control, documentation, and scalable pipeline design for deployment in production or client-facing environments</li>
<li class="MsoNormal" style="mso-list: l3 level1 lfo1; tab-stops: list .5in;">Synthesize insights from diverse data sources, including claims, prescription (LAAD), lab, EMR, and unstructured text, into clear narratives driving client decisions tailored to patient, HCP, and market contexts</li>
<li class="MsoNormal" style="mso-list: l3 level1 lfo1; tab-stops: list .5in;">Collaborate with consultants, domain experts, and engineers to structure analytical workflows that answer complex commercial or clinical questions.</li>
<li class="MsoNormal" style="mso-list: l3 level1 lfo1; tab-stops: list .5in;">Present findings and insights to internal and client stakeholders in a clear, structured, and actionable manner.</li>
<li class="MsoNormal" style="mso-list: l3 level1 lfo1; tab-stops: list .5in;">Actively participate in client discussions, supporting solution development and storyboarding for business audiences</li>
<li class="MsoNormal" style="mso-list: l3 level1 lfo1; tab-stops: list .5in;">Contribute to internal capability building through reusable ML assets, accelerators, and documentation to strengthen the team’s solution portfolio.</li>
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<p class="MsoNormal"><b>Required Skills</b></p>
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<li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Strong hands-on experience in Python, PySpark, and SQL for manipulating and handling large structured and unstructured datasets.</li>
<li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Strong foundation in machine learning algorithms, feature engineering, model tuning, and evaluation techniques</li>
<li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Proficiency in <b>data visualization</b> (Power BI, Tableau, MS Office suite or equivalent) and in translating analytical results effectively.</li>
<li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Ability to structure ambiguous business problems, design analytical roadmaps, and communicate insights effectively to both technical and non-technical stakeholders.</li>
<li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Strong collaboration and project-management skills for coordinating across multi-disciplinary teams.</li>
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<p class="MsoNormal"><b>Preferred Skills</b></p>
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<li class="MsoNormal" style="mso-list: l1 level1 lfo3; tab-stops: list .5in;">Prior experience in the pharmaceutical or life sciences industry, with familiarity across structured data sources such as LAAD, Lab, Sales, and unstructured datasets (e.g., market research, physician notes, publications).</li>
<li class="MsoNormal" style="mso-list: l1 level1 lfo3; tab-stops: list .5in;">Experience with R, Rshiny, and data platforms such as Databricks, AWS, Azure, or Snowflake is an advantage.</li>
<li class="MsoNormal" style="mso-list: l1 level1 lfo3; tab-stops: list .5in;">Exposure to MLOps frameworks, including MLflow, Docker, Airflow, or CI/CD pipelines, to automate model training, deployment, and monitoring in scalable production environments.</li>
<li class="MsoNormal" style="mso-list: l1 level1 lfo3; tab-stops: list .5in;">Experience mentoring junior analysts or collaborating in cross-functional data science teams.</li>
<li class="MsoNormal" style="mso-list: l1 level1 lfo3; tab-stops: list .5in;"><b>Qualifications</b></li>
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<li class="MsoNormal" style="mso-list: l2 level1 lfo4; tab-stops: list .5in;">Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or related fields.</li>
<li class="MsoNormal" style="mso-list: l2 level1 lfo4; tab-stops: list .5in;">4-6 years of professional experience in data science, analytics, or advanced modeling roles</li>
<li class="MsoNormal" style="mso-list: l2 level1 lfo4; tab-stops: list .5in;">Proven ability to balance analytical rigor with business understanding, delivering models that are explainable, actionable, and production-ready</li>
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