Role & responsibilities Looking for following Technical Expertise 1. Highly proficient in Python programming. 2. Strong understanding of data science algorithms, including classical machine learning, deep learning, and data preprocessing. 3. Experience with signal processing for digital data and statistical analysis of digital biomarker datasets. Day to day responsibilities: 1. Leverage digital signal processing and machine learning techniques to transform raw signals into actionable digital measures, from raw sensor data collected in key development programs. 2. Utilize statistical algorithms to evaluate potential digital measures through comparison with patient-reported outcomes (PROs) or clinical scores. 3. Contribute towards delivery of potential digital measures for consideration as digital endpoints. 4. Conduct thorough literature reviews and contribute to the development of Statistical Analysis Plans 2 of 2 (SAP) documents. 5. Engage in scientific writing by documenting and reporting analysis results for relevant projects and datasets.
Role Overview: We are seeking a highly capable and detail-oriented Commercial Finance Analyst based in India to support the Commercial Finance Directors, broader Finance team and commercial operating units. This role is critical in delivering accurate, timely, and insightful financial data and analysis to support business decision-making across projects, business units, and strategic initiatives. The ideal candidate will bring strong analytical skills, advanced Excel proficiency, and a solid understanding of financial systems and data workflows. This role is perfect for someone who thrives in a fast-paced environment and is passionate about using data and technology to drive better business outcomes. Key Responsibilities: Month-End and Financial Reporting Execute month-end close tasks including: Project revenue recognition, adjustments, and accruals Accrued and Deferred income reporting Revenue and cost of sales reconciliations (subject to data access permissions) Deliver BU-level reporting packs, including operational slides for BU reviews Ingest and validate Pulse data for reporting accuracy Project & Forecasting Support Support the budgeting and forecasting process by integrating insights from senior stakeholders into models (e.g., headcount changes, billability, rate updates) Maintain and update forecast models and associated reporting tables/slides Collaborate with PMs, HR, and cross-functional teams to ensure accurate project and people data classification Ad Hoc Analysis & Business Support Respond to ad hoc data and reporting requests from business stakeholders (e.g., RFIs) Provide clear, concise answers to project and BU-level financial queries Ensure high standards of spreadsheet hygiene and data integrity Data & Systems Responsibilities: Data Management & Automation Build and maintain automated data pipelines and reporting tools to streamline recurring tasks Implement data validation and reconciliation processes to ensure accuracy and consistency Partner with Data Engineering and IT to improve data access and infrastructure for Finance System Integration & Optimization Act as a bridge between Finance and Systems/IT teams to align financial reporting needs with system capabilities Support implementation and optimization of financial systems (e.g., DataRails, Power BI, Power Query and project management tools) Identify and drive improvements in system workflows and reporting processes Advanced Analytics & Insights Develop dashboards and visualizations using tools like Power BI, Tableau, or Looker Conduct deep-dive analyses into project profitability, resource utilization, and revenue trends Translate complex data into actionable insights for Finance and Business Unit leads Governance & Documentation Maintain clear documentation of data sources, models, and reporting logic Support data governance initiatives by ensuring consistent definitions and usage of financial metrics Candidate Profile: **Experience:** 3to5 years in a commercial finance, FP&A, or business analyst role, ideally with exposure to data systems and automation **Skills:** Advanced Excel and financial modelling Experience with BI tools (e.g., Power BI, Tableau), SQL, or Python is a plus Strong communication and collaboration skills High attention to detail and accuracy under pressure **Mindset:** Proactive, responsive, and service-oriented Comfortable working with ambiguity and evolving priorities Committed to continuous improvement and operational excellence
Purpose The role of the Principal Statistician is to provide statistical support to the statistics and programming department across a range of projects, clients and therapeutic areas. The Principal Statistician may also perform a supervisory role (e.g. line management and/or project management). Key Responsibilities Development of Methods Table: The candidate will lead the effort to develop and refine versions of the methods table, which will list methodologies required for clinical trial reporting and align those methods to existing R packages or identify gaps to be filled. Collaboration with various SMEs and regular reviews with experts will be essential. Package Review: - The candidate should be capable of conducting package reviews from a statistical methods perspective - While the candidate may not be an expert in all areas, they must proactively engage relevant experts when needed - Responsibilities include (as required) reviewing journal publications, conducting simulations (if required), and assessing whether the methods applied in the package align with the latest capabilities or improve upon current state-of-the-art tools. Prioritization of Package Evaluation: The candidate will help prioritize package evaluations, which may involve liaising with respective PS or SLS teams. They will recommend project teams based on available alternatives in the methods table, which will involve interaction with SMEs and package development teams. Strategic Communications: This individual will partner with client on communications at the Stats VP level, highlighting progress, focus areas, and key updates. Desired Capabilities: Strong statistical methods expertise with the ability to quickly learn and apply new methodologies. Solid knowledge of clinical study reporting, including inferential and modeling perspectives. Proficiency in R, with practical experience using diverse R packages. Working knowledge of SAS, ideally with an understanding of how Stats PROC aligns with statistical methods to help identify corresponding R packages. Technical: Perform technical review and provide input into clinical trial documents including protocols, CRFs, CSRs Author and review study SAP, TFL shells and dataset specifications Support study and/or compound level activities advising on study design and statistical issues across phases and therapeutic areas Author, validate and document SAS programs for datasets, TFLs and macros, applying good programming practice Application of complex statistical techniques (e.g. mixed effects, non-linear modelling, Bayesian, advanced survival), model checking and interpretation Identify and implement appropriate sample size method using software or simulations Identify data and standards issues and resolve or escalate as appropriate Awareness of emerging standards and associated impact to ongoing and future planned trials Maintain proficiency in statistical methodology Maintain study master file documents and any other documents that are required to be audit ready People Management: Line management of statisticians, programmers and other technical staff. Accountable for overall performance of direct reports Provide coaching and mentoring of staff to achieve excellence. Direct employee career development and ensure line reports receive appropriate training to perform their day-to-day jobs Interview and effectively on-board and integrate new staff members Provide statistical technical leadership and coaching Project Management: Oversight of key client projects/portfolios. To include: Being Veramed Project Manager on client accounts and projects Maintain the project plan o Proactive management of resource, scope change and risks Manage the delivery of projects to budget Manage client expectations and issue resolution . General: Lead internal and client study, project and cross functional team meetings effectively Present study updates internally and at client meetings Share scientific, technical and practical knowledge within the team and with colleagues Perform work in full compliance with applicable legislation, regulations, company policies, procedures, and training Build effective collaborative working relationships with internal and client team members Ensure learnings are shared across projects or studies Develop and provide internal technical training where appropriate Lead process improvement initiatives Minimum Qualification Requirements MSc or PhD in Statistics/Biostatistics (or equivalent) At least 7 years of relevant industry experience Other Information/Additional Requirements Understanding of clinical drug development process, relevant disease areas, endpoints and different study designs Awareness of industry and project standards & ICH guidelines Excellent verbal and written communication skills Interpersonal/teamwork skills for effective interactions Proficiency in data handling using SAS or other statistical software (e.g. R) Self-management skills with a focus on results for timely and accurate completion of competing deliverables Demonstrated problem solving ability and attention to detail Ability to work independently and as part of a team Ability to manage a portfolio of projects and/or people Specific Key Responsibilities:
Purpose The role of the Principal Programmer is to provide programming support to the statistics and programming department across a range of projects, clients and therapeutic areas. Key Responsibilities The study programmer position will be responsible for manipulating large databases and generating reports to enable analysts to explore real world healthcare data assets. Candidates must have excellent SAS and SQL programming skills and the ability to implement complex logic. Candidates must be comfortable with creating complex analysis data sets derived from various data sources with a careful eye for outliers and errors. Prior experience building patient cohorts and evaluating patient healthcare events in large databases and using observational research methods such as epidemiology and statistical methods is strongly desired. SAS is also fine. R is preferred and is a must have. We are open to any therapeutic area experience. The team primarily supports rare diseases so if we present candidates with this area of expertise then that will be a plus, but no emphasis on therapeutic area. Real World Healthcare claims database experience is must. Any equivalent EU database experience to US Market scan/Optum is fine. OMOP-Common data model experience is a huge plus. We are fine with someone with even 1 year experience, familiar with this experience. SQL is must specially querying and extracting from database. Strong communication, time management, enthusiasm and documentation skills are essential in this position. Technical Proficient in R and SQL programming - Expertise in Oncology databases such as Flatiron, COTA - Has good understanding of Oncology specific analyses such as Line of Therapy algorithms, Survival analysis, different statistical models - Preferable to have R Shiny or Instant Health Data (IHD) experience - Experience with Analytic Datasets, patient cohorts is good to have. General Lead internal and client study team meetings effectively Present study updates internally and at client meetings Share scientific, technical and practical knowledge within the team and with colleagues Perform work in full compliance with applicable legislation, regulations, company policies, procedures, and training Build effective collaborative working relationships with internal and client team members Seek opportunities to develop innovative ideas, sharing when appropriate Line management or mentorship of more junior team members Contribution to development of internal training materials Contribution to internal process improvement initiatives Minimum Qualification Requirements Bachelors degree in computer science, Statistics, Mathematics, or other subject with high statistical content Minimum 7-8 years SAS statistical programming experience Database programming using SQL Experience with advanced statistical methods such as survival and regression Experience with real world healthcare claims and EHR data such as MarketScan, Optum and Medicare databases Other Information/Additional Requirements Master’s degree in Epidemiology, Biostatistics, Computer Science, or other subject with high statistical content Training or experience using the OMOP common data model Training or experience with Python, R, Databricks or other cloud-based software Pharmaceutical industry experience Training or experience in epidemiological methods
Purpose The role of the Principal Programmer is to provide programming support to the statistics and programming department across a range of projects, clients and therapeutic areas. The Principal Programmer may also perform a supervisory role (e.g. line management and/or project management). Key Responsibilities Supporting with CDISC implementation of studies with Real world data QC of SDTM/ADaM datasets as required Review the aCRF, Specs, relevant documentation like SDRG/ADRG, Define.xml as relevant Expertise working across different disease areas like Oncology, Vaccines, Respiratory etc Guide Real World Programmers on NIS with CDISC expectations Technical: Perform review of clinical trial documents including protocols, SAPs, CRFs, CSRs Author, review and approve study TFL shells and dataset specifications Author, validate and document SAS programs for datasets, TFLs and macros, applying good programming practice Identify data issues and outliers Complete, review and approve CDISC Validation tool reports Identify data and standards issues and resolve or escalate as appropriate Awareness of emerging standards and associated impact to ongoing and future planned trials Maintain proficiency in SAS and awareness of developments Maintain study master file documents and any other documents that are required to be audit ready People Management: Line management of statisticians, programmers and other technical staff. Accountable for overall performance of direct reports Provide coaching and mentoring of staff to achieve excellence. Direct employee career development and ensure line reports receive appropriate training to perform their day-to-day jobs Interview and effectively on-board and integrate new staff members Provide programming technical leadership and coaching Project Management: Oversight of key client projects/portfolios. To include: Being Veramed Project Manager on client accounts and projects Maintain the project plan Proactive management of resource, scope change and risks Manage the delivery of projects to budget Manage client expectations and issue resolution General: Lead internal and client study, project and cross functional team meetings effectively Present study updates internally and at client meetings Share scientific, technical and practical knowledge within the team and with colleagues Perform work in full compliance with applicable legislation, regulations, company policies, procedures, and training Build effective collaborative working relationships with internal and client team members Ensure learnings are shared across projects or studies Develop and provide internal technical training where appropriate Lead process improvement initiatives Minimum Qualification Requirements BSc, MSc or PhD in numerical discipline (or relevant equivalent industry experience) At least 8 years of relevant industry experience Other Information/Additional Requirements Understanding of clinical drug development process, relevant disease areas, endpoints and study designs Awareness of industry and project standards & ICH guidelines Excellent verbal and written communication skills Interpersonal/teamwork skills for effective interactions Proficiency in data handling using SAS or other statistical software (e.g. R) Self-management skills with a focus on results for timely and accurate completion of competing deliverables Demonstrated problem solving ability and attention to detail Ability to work independently and as part of a team Ability to manage a portfolio of projects and/or people