Planful

About Us

Planful is the pioneer of financial performance management cloud software. The Planful platform, which helps businesses drive peak financial performance, is used around the globe to streamline business-wide planning, budgeting, consolidations, reporting, and analytics. Planful empowers finance, accounting, and business users to plan confidently, close faster, and report accurately. More than 1,300 customers, including 23andMe, Bose, Boston Red Sox, Five Guys, and Zappos, rely on Planful to accelerate cycle times, increase productivity, and improve accuracy. Planful is a private company backed by Vector Capital, a leading global private equity firm. Learn more at www.planful.com.

About the Role

We are seeking a talented and experienced Data Scientist to join our Hyderabad, India Planful office. As a Data Scientist, you will play a pivotal role in developing and enhancing data-driven insights, predictive models, and analytical tools to drive actionable business outcomes for our clients. You will collaborate closely with cross-functional teams including product management, engineering, and customer success to deliver innovative solutions that address complex financial challenges.

Responsibilities

• Develop natural language processing abilities in the product to provide avenues to end users to interact with the Planful systems using natural language.
• Building in-house LLM models to convert from natural language to system-specific instructions and to support the summarization features.
• Keep pace with fast changing AI landscape, filter out the relevant details about the new innovations and apply them to solve our challenges.
• Foster relationships with engineering and product management by being proactive, displaying a thorough understanding of the business processes and by recommending innovative solutions.
• Communicate project output in terms of customer value, business objectives, and product opportunity.
• Promote data science methods and processes across functions and mentor budding data science enthusiasts

What you Bring to the Table

• Minimum of 8+ years of experience in developing distributed applications (financial domain preferred) and/or BI applications.
• Experience with developing and deploying Natural Language Processing/Understanding applications
• Experience using libraries like NLTK, Spacy for NER and developing RNN (LSTM /GRU) based models to process the natural language statements..
• Experience in building TF-IDF based logistical models to classify the text to the desired categories.
• One must have experience using Huggingface, Langchain, PyTorch, vector databases.
• Knowledge of techniques like RAG, Quantization, and transfer learning is desired.
• Familiarity with Google deep learning libraries like Keras and Tensorflow is a plus.
• Experience working with remote and global teams.
• Applicant must be able to write the code to build POCs.
• Results driven with a positive can-do attitude
• Master’s degree in Computer Science, Engineering, Applied Mathematics, or statistics
• Proven experience as a Data Scientist or Data Analyst
• Minimum of 5 years of hands-on experience with languages like SQL, python/R
• Supreme problem skills
• Excellent communication and presentation skills

Why Planful 

Planful exists to enrich the world by helping our customers and our people achieve peak performance. To foster the best in-class work we’re so proud of, we’ve created a best-in-class culture, including:

• 2 Volunteer days, Birthday PTO, and quarterly company Wellness Days
• 3 months supply of diapers and meal deliveries for the first month of your Maternity/Paternity leave
• Annual Planful Palooza, our in-person, company-wide culture kickoff
• Company-wide Mentorship program with Executive sponsorship of CFO and Manager-specific monthly training programs
• Employee Resource Groups such as Women of Planful, LatinX at Planful, Parents of Planful, and many more. We encourage our teammates to bring their authentic selves to the team, and have full support in creating new ERGs & communities along the way