Executive Account Sales (US-based, B2B SaaS, ERP)

Technology Industry

Executive Account Sales (US-based, B2B SaaS, ERP)

Peak Hire Solutions

Company

Home

Executive Account Sales (US-based, B2B SaaS, ERP)

at Technology Industry

Agency job

via Peak Hire Solutions

4 - 13 yrs

₹40L - ₹90L / yr

Remote, New York

Skills

B2B Marketing

SaaS

Enterprise Resource Planning (ERP)

Sales

Market Research

Market analysis

Go-to-market strategy

Market intelligence

Market Automation Tools

Market segmentation

Market share

Market development

Go to market

Market risk

ROLE & RESPONSIBILITIES:

Pipeline ownership – Drive qualified opportunities from first meeting to close.
Discovery & demos – Run high-impact discovery calls and demos, often tailored with Engineering & CS.
Pilots that win – Steer complex pilots with flawless follow-through, project management across internal teams and prospects.
Negotiation & closing – Go toe-to-toe with legacy vendors, show Company’s value, and win.
Implementation partnership – Ensure a smooth go-live with Engineering & Solutions.
Mentorship – Help existing AEs level up in enterprise sales, joining as a senior persona when needed.
CRM & process excellence – Instill rigor for pipeline visibility and repeatability.
Voice of the customer – Champion customer feedback to shape Product & GTM.
Future team-building – Hire and scale the North America AE org over time.

IDEAL CANDIDATE:

6+ years of experience selling B2B SaaS to US customers.
Previous experience selling to Mid-Market and Enterprise customers: Closed Enterprise deals, $75k+ ACV, ideally $100k+.
Prior experience in coaching/managing junior AEs is a strong plus.
Ability to build, manage and motivate a team.
Prior success as one of the first AEs at a startup; comfortable working in a fast-paced, early-stage startup environment.
Track record of consistently beating your quota.
Solid hustle and entrepreneurial mindset; Thrive under the uncertainty that comes with an early-stage setup.
Strong project management skills and proactiveness, given the long sales cycle and pilot (free trials) heavy nature of deals.
Strong first-principles understanding of sales processes (e.g. MEDDPICC).
Self-driven individual with high ownership and strong work ethic.
Previous entrepreneurial experience is a huge plus.
Not taking yourself too seriously.

PERKS, BENEFITS AND WORK CULTURE:

Variable: Based on performance
ESOPs (for full time roles)
Remote (USA)

BENEFITS (FOR FULL-TIME ROLES):

Health insurance
Generous vacation policy
Learning and development budget
Team events and company offsites
Maternity and Paternity benefits
Company Laptop
Friday game nights

ROLE & RESPONSIBILITIES:

Pipeline ownership – Drive qualified opportunities from first meeting to close.
Discovery & demos – Run high-impact discovery calls and demos, often tailored with Engineering & CS.
Pilots that win – Steer complex pilots with flawless follow-through, project management across internal teams and prospects.
Negotiation & closing – Go toe-to-toe with legacy vendors, show Company’s value, and win.
Implementation partnership – Ensure a smooth go-live with Engineering & Solutions.
Mentorship – Help existing AEs level up in enterprise sales, joining as a senior persona when needed.
CRM & process excellence – Instill rigor for pipeline visibility and repeatability.
Voice of the customer – Champion customer feedback to shape Product & GTM.
Future team-building – Hire and scale the North America AE org over time.

IDEAL CANDIDATE:

6+ years of experience selling B2B SaaS to US customers.
Previous experience selling to Mid-Market and Enterprise customers: Closed Enterprise deals, $75k+ ACV, ideally $100k+.
Prior experience in coaching/managing junior AEs is a strong plus.
Ability to build, manage and motivate a team.
Prior success as one of the first AEs at a startup; comfortable working in a fast-paced, early-stage startup environment.
Track record of consistently beating your quota.
Solid hustle and entrepreneurial mindset; Thrive under the uncertainty that comes with an early-stage setup.
Strong project management skills and proactiveness, given the long sales cycle and pilot (free trials) heavy nature of deals.
Strong first-principles understanding of sales processes (e.g. MEDDPICC).
Self-driven individual with high ownership and strong work ethic.
Previous entrepreneurial experience is a huge plus.
Not taking yourself too seriously.

PERKS, BENEFITS AND WORK CULTURE:

Variable: Based on performance
ESOPs (for full time roles)
Remote (USA)

BENEFITS (FOR FULL-TIME ROLES):

Health insurance
Generous vacation policy
Learning and development budget
Team events and company offsites
Maternity and Paternity benefits
Company Laptop
Friday game nights

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Demand forecasting

Optimization

WyngCommerce is building state of the art AI software for the Global Consumer Brands & Retailers to enable best-in-class customer experiences. Our vision is to democratise machine learning algorithms for our customers and help them realise dramatic improvements in speed, cost and flexibility. Backed by a clutch of prominent angel investors & having some of the category leaders in the retail industry as clients, we are looking to hire for our data science team. The data science team at WyngCommerce is on a mission to challenge the norms and re-imagine how retail business should be run across the world. As a Senior Data Scientist in the team, you will be driving and owning the thought leadership and impact on one of our core data science problems. You will work collaboratively with the founders, clients and engineering team to formulate complex problems, run Exploratory Data Analysis and test hypotheses, implement ML-based solutions and fine tune them with more data. This is a high impact role with goals that directly impact our business. Your Role & Responsibilities - - Lead and Own the Thought Process on one or more of our core Data Science problems e.g. Product Clustering, Intertemporal Optimization, etc. - Actively participate and challenge assumptions in translating ambiguous business problems into one or more ML/optimization problems - Implement data-driven solutions based on advanced ML and optimization algorithms to address business problems - Research, experiment, and innovate ML/statistical approaches in various application areas of interest and contribute to IP - Partner with engineering teams to build scalable, efficient, automated ML-based pipelines (training/evaluation/monitoring) - Deploy, maintain, and debug ML/decision models in production environment - Analyze and assess data to ensure high data quality and correctness of downstream processes - Define and own metrics on solution quality, data quality and stability of ML pipelines - Communicate results to stakeholders and present data/insights to participate in and drive decision making Desired Skills & Experiences - - Bachelors or Masters in a quantitative field from a top tier college. - Minimum of 3+ years experience in a data science role in a technology company - Solid mathematical background (especially in linear algebra, probability theory, optimization theory, decision theory, operations research) - Familiarity with theoretical aspects of common ML techniques (generalized linear models, ensembles, SVMs, clustering algos, graphical models, etc.), statistical tests/metrics, experiment design, and evaluation methodologies - Solid foundation in data structures, algorithms, and programming language theory - Demonstrable track record of dealing with ambiguity, prioritizing needs, bias for iterative learning, and delivering results in a dynamic environment with minimal guidance - Hands-on experience in at least one of the focus areas of WyngCommerce Data Science team: (a) Product Clustering, (b) Demand Forecasting, (c) Intertemporal Optimization, (d) Reinforcement Learning, (e) Transfer Learning - Good programming skills (fluent in Java/Python/SQL) with experience of using common ML toolkits (e.g., sklearn, tensor flow, keras, nltk) to build models for real world problems - Computational thinking and familiarity with practical application requirements (e.g., latency, memory, processing time) - Experience using Cloud-based ML platforms (e.g., AWS Sagemaker, Azure ML), Cloud-based data storage, and deploying ML models in product environment in collaboration with engineering teams - Excellent written and verbal communication skills for both technical and non-technical audiences - (Plus Point) Experience of applying ML / other techniques in the domain of supply chain - and particularly in retail - for inventory optimization, demand forecasting, assortment planning, and other such problems - (Nice to have) Research experience and publications in top ML/Data science conferences

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