Data Scientist - Revenue Growth Management

About the company

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We oer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. Youll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.

Offices: New York | Dallas | San Francisco | Lima | Bengaluru

The below role is for our Bengaluru office (Hybrid)

About the Role:

You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning, we would like to talk to you.

Role: Sr Data Scientist / Associate Lead Data Scientist / Lead Data Scientist

Experience: 4 - 9 Years

Mandate Skills & Competencies:

• Experience in Programming (Python, R, SQL, NoSQL, Spark) with ML tools & Cloud Technology (AWS, Azure, GCP)
• Experience in Python libraries such as NumPy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc.
• Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making.
• Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.)
• Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc.
• Contribute to internal product development initiatives related to data science.
• Develop data science roadmap, and guide data scientist to meet their deliverables.
• Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction.
• Proven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights
• Drive excellent project management required to deliver complex projects, including effort/time estimation.
• Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy
• Define Technology/ Strategy and Roadmap for client accounts, and guides implementation of that strategy within projects
• Run regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders
• Manage the team-members, to ensure that the project plan is being adhered to over the course of the project
• Manage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates.
• Build a trusted advisor relationship with the IT management at clients and internal accounts leadership.
• Build business case for technological investments to be made for future needs and to remain competitive
• Ensure that billing and utilization of team members is maximized throughout the year

Desired Skills:

• Experience designing data science solutions to business problems
• Deep understanding of ML algorithms for common use cases in both structured and unstructured data ecosystems.
• Comfortable with large scale data processing and distributed computing
• Allocates workload among team members and by taking into consideration employee availability, skill set, and current workload when making assignments.
• Providing required inputs to sales, and pre-sales activities
• Excellent written and verbal communication skills

Desired Experience & Education:

• 4- 9 years of relevant Machine Learning experience.
• Minimum Masters Degree in Engineering, Computer Science, Mathematics, Computational Statistics, Operations Research, Machine Learning or related technical fields.